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Volume 97: International Conference on Machine Learning, 9-15 June 2019, Long Beach, California, USA
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Editors: Kamalika Chaudhuri, Ruslan Salakhutdinov
AReS and MaRS Adversarial and MMD-Minimizing Regression for SDEs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1-10
Dynamic Weights in Multi-Objective Deep Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:11-20
MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:21-29
Communication-Constrained Inference and the Role of Shared Randomness
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:30-39
Distributed Learning with Sublinear Communication
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:40-50
Communication Complexity in Locally Private Distribution Estimation and Heavy Hitters
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:51-60
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Learning Models from Data with Measurement Error: Tackling Underreporting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:61-70
TibGM: A Transferable and Information-Based Graphical Model Approach for Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:71-81
PAC Learnability of Node Functions in Networked Dynamical Systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:82-91
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Static Automatic Batching In TensorFlow
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:92-101
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Efficient Full-Matrix Adaptive Regularization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:102-110
Online Control with Adversarial Disturbances
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:111-119
Fair Regression: Quantitative Definitions and Reduction-Based Algorithms
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:120-129
Learning to Generalize from Sparse and Underspecified Rewards
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:130-140
The Kernel Interaction Trick: Fast Bayesian Discovery of Pairwise Interactions in High Dimensions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:141-150
Understanding the Impact of Entropy on Policy Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:151-160
Fairwashing: the risk of rationalization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:161-170
Adaptive Stochastic Natural Gradient Method for One-Shot Neural Architecture Search
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:171-180
Projections for Approximate Policy Iteration Algorithms
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:181-190
Validating Causal Inference Models via Influence Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:191-201
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Multi-objective training of Generative Adversarial Networks with multiple discriminators
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:202-211
Graph Element Networks: adaptive, structured computation and memory
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:212-222
Analogies Explained: Towards Understanding Word Embeddings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:223-231
Infinite Mixture Prototypes for Few-shot Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:232-241
A Convergence Theory for Deep Learning via Over-Parameterization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:242-252
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Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:253-262
Bounding User Contributions: A Bias-Variance Trade-off in Differential Privacy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:263-271
Explaining Deep Neural Networks with a Polynomial Time Algorithm for Shapley Value Approximation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:272-281
Scaling Up Ordinal Embedding: A Landmark Approach
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:282-290
Sorting Out Lipschitz Function Approximation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:291-301
Sparse Multi-Channel Variational Autoencoder for the Joint Analysis of Heterogeneous Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:302-311
Unsupervised Label Noise Modeling and Loss Correction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:312-321
Fine-Grained Analysis of Optimization and Generalization for Overparameterized Two-Layer Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:322-332
Distributed Weighted Matching via Randomized Composable Coresets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:333-343
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Stochastic Gradient Push for Distributed Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:344-353
Bayesian Optimization of Composite Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:354-363
Linear-Complexity Data-Parallel Earth Mover’s Distance Approximations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:364-373
Benefits and Pitfalls of the Exponential Mechanism with Applications to Hilbert Spaces and Functional PCA
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:374-384
Feature Grouping as a Stochastic Regularizer for High-Dimensional Structured Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:385-394
Beyond the Chinese Restaurant and Pitman-Yor processes: Statistical Models with double power-law behavior
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:395-404
Scalable Fair Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:405-413
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:414-423
Provable Guarantees for Gradient-Based Meta-Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:424-433
Open-ended learning in symmetric zero-sum games
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:434-443
Concrete Autoencoders: Differentiable Feature Selection and Reconstruction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:444-453
HOList: An Environment for Machine Learning of Higher Order Logic Theorem Proving
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:454-463
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Structured agents for physical construction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:464-474
Learning to Route in Similarity Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:475-484
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A Personalized Affective Memory Model for Improving Emotion Recognition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:485-494
Scale-free adaptive planning for deterministic dynamics & discounted rewards
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:495-504
Pareto Optimal Streaming Unsupervised Classification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:505-514
Categorical Feature Compression via Submodular Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:515-523
Noise2Self: Blind Denoising by Self-Supervision
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:524-533
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Efficient optimization of loops and limits with randomized telescoping sums
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:534-543
Recurrent Kalman Networks: Factorized Inference in High-Dimensional Deep Feature Spaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:544-552
Switching Linear Dynamics for Variational Bayes Filtering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:553-562
Active Learning for Probabilistic Structured Prediction of Cuts and Matchings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:563-572
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Invertible Residual Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:573-582
Greedy Layerwise Learning Can Scale To ImageNet
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:583-593
Overcoming Multi-model Forgetting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:594-603
Optimal Kronecker-Sum Approximation of Real Time Recurrent Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:604-613
Adversarially Learned Representations for Information Obfuscation and Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:614-623
Bandit Multiclass Linear Classification: Efficient Algorithms for the Separable Case
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:624-633
Analyzing Federated Learning through an Adversarial Lens
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:634-643
Optimal Continuous DR-Submodular Maximization and Applications to Provable Mean Field Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:644-653
More Efficient Off-Policy Evaluation through Regularized Targeted Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:654-663
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A Kernel Perspective for Regularizing Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:664-674
Rethinking Lossy Compression: The Rate-Distortion-Perception Tradeoff
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:675-685
Correlated bandits or: How to minimize mean-squared error online
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:686-694
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Adversarial Attacks on Node Embeddings via Graph Poisoning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:695-704
Online Variance Reduction with Mixtures
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:705-714
Compositional Fairness Constraints for Graph Embeddings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:715-724
Unreproducible Research is Reproducible
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:725-734
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Blended Conditonal Gradients
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:735-743
Coresets for Ordered Weighted Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:744-753
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Target Tracking for Contextual Bandits: Application to Demand Side Management
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:754-763
Active Manifolds: A non-linear analogue to Active Subspaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:764-772
Conditioning by adaptive sampling for robust design
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:773-782
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:783-792
Deep Counterfactual Regret Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:793-802
Understanding the Origins of Bias in Word Embeddings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:803-811
Low Latency Privacy Preserving Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:812-821
Why do Larger Models Generalize Better? A Theoretical Perspective via the XOR Problem
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:822-830
Adversarial examples from computational constraints
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:831-840
Self-similar Epochs: Value in arrangement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:841-850
Learning Generative Models across Incomparable Spaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:851-861
Rates of Convergence for Sparse Variational Gaussian Process Regression
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:862-871
What is the Effect of Importance Weighting in Deep Learning?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:872-881
A Quantitative Analysis of the Effect of Batch Normalization on Gradient Descent
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:882-890
Accelerated Linear Convergence of Stochastic Momentum Methods in Wasserstein Distances
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:891-901
Active Embedding Search via Noisy Paired Comparisons
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:902-911
Dynamic Learning with Frequent New Product Launches: A Sequential Multinomial Logit Bandit Problem
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:912-920
Competing Against Nash Equilibria in Adversarially Changing Zero-Sum Games
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:921-930
Automated Model Selection with Bayesian Quadrature
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:931-940
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Learning Action Representations for Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:941-950
Dynamic Measurement Scheduling for Event Forecasting using Deep RL
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:951-960
On Symmetric Losses for Learning from Corrupted Labels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:961-970
Online learning with kernel losses
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:971-980
Neural Network Attributions: A Causal Perspective
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:981-990
PAC Identification of Many Good Arms in Stochastic Multi-Armed Bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:991-1000
Nearest Neighbor and Kernel Survival Analysis: Nonasymptotic Error Bounds and Strong Consistency Rates
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1001-1010
Stein Point Markov Chain Monte Carlo
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1011-1021
Particle Flow Bayes’ Rule
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1022-1031
Proportionally Fair Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1032-1041
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Information-Theoretic Considerations in Batch Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1042-1051
Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1052-1061
Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1062-1070
A Gradual, Semi-Discrete Approach to Generative Network Training via Explicit Wasserstein Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1071-1080
Transferability vs. Discriminability: Batch Spectral Penalization for Adversarial Domain Adaptation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1081-1090
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Fast Incremental von Neumann Graph Entropy Computation: Theory, Algorithm, and Applications
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1091-1101
Katalyst: Boosting Convex Katayusha for Non-Convex Problems with a Large Condition Number
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1102-1111
Multivariate-Information Adversarial Ensemble for Scalable Joint Distribution Matching
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1112-1121
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Robust Decision Trees Against Adversarial Examples
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1122-1131
RaFM: Rank-Aware Factorization Machines
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1132-1140
Control Regularization for Reduced Variance Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1141-1150
Predictor-Corrector Policy Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1151-1161
Variational Inference for sparse network reconstruction from count data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1162-1171
Random Walks on Hypergraphs with Edge-Dependent Vertex Weights
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1172-1181
Neural Joint Source-Channel Coding
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1182-1192
Beyond Backprop: Online Alternating Minimization with Auxiliary Variables
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1193-1202
Unifying Orthogonal Monte Carlo Methods
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1203-1212
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Probability Functional Descent: A Unifying Perspective on GANs, Variational Inference, and Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1213-1222
MeanSum: A Neural Model for Unsupervised Multi-Document Abstractive Summarization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1223-1232
Weak Detection of Signal in the Spiked Wigner Model
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1233-1241
New results on information theoretic clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1242-1251
Sensitivity Analysis of Linear Structural Causal Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1252-1261
Dimensionality Reduction for Tukey Regression
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1262-1271
On Medians of (Randomized) Pairwise Means
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1272-1281
Quantifying Generalization in Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1282-1289
Empirical Analysis of Beam Search Performance Degradation in Neural Sequence Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1290-1299
Learning Linear-Quadratic Regulators Efficiently with only $\sqrtT$ Regret
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1300-1309
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Certified Adversarial Robustness via Randomized Smoothing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1310-1320
Gauge Equivariant Convolutional Networks and the Icosahedral CNN
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1321-1330
CURIOUS: Intrinsically Motivated Modular Multi-Goal Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1331-1340
A fully differentiable beam search decoder
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1341-1350
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Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1351-1360
Adjustment Criteria for Generalizing Experimental Findings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1361-1369
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Online Learning with Sleeping Experts and Feedback Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1370-1378
Active Learning with Disagreement Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1379-1387
Shape Constraints for Set Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1388-1396
Training Well-Generalizing Classifiers for Fairness Metrics and Other Data-Dependent Constraints
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1397-1405
Monge blunts Bayes: Hardness Results for Adversarial Training
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1406-1415
Boosted Density Estimation Remastered
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1416-1425
Submodular Cost Submodular Cover with an Approximate Oracle
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1426-1435
Flexibly Fair Representation Learning by Disentanglement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1436-1445
Anytime Online-to-Batch, Optimism and Acceleration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1446-1454
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Matrix-Free Preconditioning in Online Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1455-1464
Minimal Achievable Sufficient Statistic Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1465-1474
Open Vocabulary Learning on Source Code with a Graph-Structured Cache
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1475-1485
The Value Function Polytope in Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1486-1495
Bayesian Optimization Meets Bayesian Optimal Stopping
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1496-1506
Policy Certificates: Towards Accountable Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1507-1516
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Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1517-1527
A Kernel Theory of Modern Data Augmentation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1528-1537
TarMAC: Targeted Multi-Agent Communication
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1538-1546
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Teaching a black-box learner
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1547-1555
Stochastic Deep Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1556-1565
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Learning-to-Learn Stochastic Gradient Descent with Biased Regularization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1566-1575
A Multitask Multiple Kernel Learning Algorithm for Survival Analysis with Application to Cancer Biology
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1576-1585
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Learning to Convolve: A Generalized Weight-Tying Approach
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1586-1595
Sever: A Robust Meta-Algorithm for Stochastic Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1596-1606
Approximated Oracle Filter Pruning for Destructive CNN Width Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1607-1616
Noisy Dual Principal Component Pursuit
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1617-1625
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Finite-Time Analysis of Distributed TD(0) with Linear Function Approximation on Multi-Agent Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1626-1635
Trajectory-Based Off-Policy Deep Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1636-1645
Generalized No Free Lunch Theorem for Adversarial Robustness
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1646-1654
Width Provably Matters in Optimization for Deep Linear Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1655-1664
Provably efficient RL with Rich Observations via Latent State Decoding
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1665-1674
Gradient Descent Finds Global Minima of Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1675-1685
Incorporating Grouping Information into Bayesian Decision Tree Ensembles
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1686-1695
Task-Agnostic Dynamics Priors for Deep Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1696-1705
Optimal Auctions through Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1706-1715
Wasserstein of Wasserstein Loss for Learning Generative Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1716-1725
Learning interpretable continuous-time models of latent stochastic dynamical systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1726-1734
Autoregressive Energy Machines
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1735-1744
Band-limited Training and Inference for Convolutional Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1745-1754
Imitating Latent Policies from Observation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1755-1763
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Semi-Cyclic Stochastic Gradient Descent
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1764-1773
GDPP: Learning Diverse Generations using Determinantal Point Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1774-1783
Sequential Facility Location: Approximate Submodularity and Greedy Algorithm
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1784-1793
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Improved Convergence for $\ell_1$ and $\ell_∞$ Regression via Iteratively Reweighted Least Squares
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1794-1801
Exploring the Landscape of Spatial Robustness
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1802-1811
Cross-Domain 3D Equivariant Image Embeddings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1812-1822
On the Connection Between Adversarial Robustness and Saliency Map Interpretability
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1823-1832
Non-monotone Submodular Maximization with Nearly Optimal Adaptivity and Query Complexity
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1833-1842
Multi-Frequency Vector Diffusion Maps
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1843-1852
[abs][Download PDF]
Stable-Predictive Optimistic Counterfactual Regret Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1853-1862
Regret Circuits: Composability of Regret Minimizers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1863-1872
Dead-ends and Secure Exploration in Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1873-1881
Invariant-Equivariant Representation Learning for Multi-Class Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1882-1891
The advantages of multiple classes for reducing overfitting from test set reuse
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1892-1900
Decentralized Exploration in Multi-Armed Bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1901-1909
Almost surely constrained convex optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1910-1919
Online Meta-Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1920-1930
DL2: Training and Querying Neural Networks with Logic
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1931-1941
Bayesian Action Decoder for Deep Multi-Agent Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1942-1951
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1952-1962
On discriminative learning of prediction uncertainty
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1963-1971
Learning Discrete Structures for Graph Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1972-1982
Distributional Multivariate Policy Evaluation and Exploration with the Bellman GAN
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1983-1992
Approximating Orthogonal Matrices with Effective Givens Factorization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:1993-2001
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Fast and Flexible Inference of Joint Distributions from their Marginals
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2002-2011
Analyzing and Improving Representations with the Soft Nearest Neighbor Loss
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2012-2020
Diagnosing Bottlenecks in Deep Q-learning Algorithms
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2021-2030
MetricGAN: Generative Adversarial Networks based Black-box Metric Scores Optimization for Speech Enhancement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2031-2041
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Beyond Adaptive Submodularity: Approximation Guarantees of Greedy Policy with Adaptive Submodularity Ratio
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2042-2051
Off-Policy Deep Reinforcement Learning without Exploration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2052-2062
Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2063-2072
Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2073-2082
Graph U-Nets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2083-2092
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Deep Generative Learning via Variational Gradient Flow
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2093-2101
Rate Distortion For Model Compression:From Theory To Practice
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2102-2111
Demystifying Dropout
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2112-2121
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Geometric Scattering for Graph Data Analysis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2122-2131
Multi-Frequency Phase Synchronization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2132-2141
Optimal Mini-Batch and Step Sizes for SAGA
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2142-2150
SelectiveNet: A Deep Neural Network with an Integrated Reject Option
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2151-2159
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A Theory of Regularized Markov Decision Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2160-2169
DeepMDP: Learning Continuous Latent Space Models for Representation Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2170-2179
Partially Linear Additive Gaussian Graphical Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2180-2190
Learning and Data Selection in Big Datasets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2191-2200
Improved Parallel Algorithms for Density-Based Network Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2201-2210
Recursive Sketches for Modular Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2211-2220
An Instability in Variational Inference for Topic Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2221-2231
An Investigation into Neural Net Optimization via Hessian Eigenvalue Density
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2232-2241
Data Shapley: Equitable Valuation of Data for Machine Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2242-2251
Efficient Dictionary Learning with Gradient Descent
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2252-2259
A Tree-Based Method for Fast Repeated Sampling of Determinantal Point Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2260-2268
Learning to Groove with Inverse Sequence Transformations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2269-2279
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Adversarial Examples Are a Natural Consequence of Test Error in Noise
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2280-2289
Discovering Conditionally Salient Features with Statistical Guarantees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2290-2298
Estimating Information Flow in Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2299-2308
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Amortized Monte Carlo Integration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2309-2318
Online Algorithms for Rent-Or-Buy with Expert Advice
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2319-2327
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The information-theoretic value of unlabeled data in semi-supervised learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2328-2336
Efficient Training of BERT by Progressively Stacking
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2337-2346
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Quantile Stein Variational Gradient Descent for Batch Bayesian Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2347-2356
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Obtaining Fairness using Optimal Transport Theory
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2357-2365
Combining parametric and nonparametric models for off-policy evaluation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2366-2375
Counterfactual Visual Explanations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2376-2384
Adaptive Sensor Placement for Continuous Spaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2385-2393
A Statistical Investigation of Long Memory in Language and Music
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2394-2403
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Automatic Posterior Transformation for Likelihood-Free Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2404-2414
Learning to Optimize Multigrid PDE Solvers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2415-2423
Multi-Object Representation Learning with Iterative Variational Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2424-2433
Graphite: Iterative Generative Modeling of Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2434-2444
Fast Algorithm for Generalized Multinomial Models with Ranking Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2445-2453
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Towards a Deep and Unified Understanding of Deep Neural Models in NLP
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2454-2463
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An Investigation of Model-Free Planning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2464-2473
Humor in Word Embeddings: Cockamamie Gobbledegook for Nincompoops
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2474-2483
Simple Black-box Adversarial Attacks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2484-2493
Exploring interpretable LSTM neural networks over multi-variable data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2494-2504
Learning to Exploit Long-term Relational Dependencies in Knowledge Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2505-2514
Memory-Optimal Direct Convolutions for Maximizing Classification Accuracy in Embedded Applications
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2515-2524
IMEXnet A Forward Stable Deep Neural Network
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2525-2534
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On The Power of Curriculum Learning in Training Deep Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2535-2544
Trading Redundancy for Communication: Speeding up Distributed SGD for Non-convex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2545-2554
Learning Latent Dynamics for Planning from Pixels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2555-2565
Neural Separation of Observed and Unobserved Distributions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2566-2575
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Grid-Wise Control for Multi-Agent Reinforcement Learning in Video Game AI
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2576-2585
Dimension-Wise Importance Sampling Weight Clipping for Sample-Efficient Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2586-2595
Complexity of Linear Regions in Deep Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2596-2604
Importance Sampling Policy Evaluation with an Estimated Behavior Policy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2605-2613
Doubly-Competitive Distribution Estimation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2614-2623
Random Shuffling Beats SGD after Finite Epochs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2624-2633
Submodular Maximization beyond Non-negativity: Guarantees, Fast Algorithms, and Applications
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2634-2643
Per-Decision Option Discounting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2644-2652
Submodular Observation Selection and Information Gathering for Quadratic Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2653-2662
Understanding and Controlling Memory in Recurrent Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2663-2671
On the Impact of the Activation function on Deep Neural Networks Training
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2672-2680
Provably Efficient Maximum Entropy Exploration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2681-2691
On the Long-term Impact of Algorithmic Decision Policies: Effort Unfairness and Feature Segregation through Social Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2692-2701
Graph Resistance and Learning from Pairwise Comparisons
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2702-2711
Using Pre-Training Can Improve Model Robustness and Uncertainty
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2712-2721
Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2722-2730
Population Based Augmentation: Efficient Learning of Augmentation Policy Schedules
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2731-2741
Collective Model Fusion for Multiple Black-Box Experts
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2742-2750
Connectivity-Optimized Representation Learning via Persistent Homology
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2751-2760
Better generalization with less data using robust gradient descent
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2761-2770
Emerging Convolutions for Generative Normalizing Flows
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2771-2780
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Nonconvex Variance Reduced Optimization with Arbitrary Sampling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2781-2789
Parameter-Efficient Transfer Learning for NLP
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2790-2799
Stay With Me: Lifetime Maximization Through Heteroscedastic Linear Bandits With Reneging
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2800-2809
Finding Mixed Nash Equilibria of Generative Adversarial Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2810-2819
Classification from Positive, Unlabeled and Biased Negative Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2820-2829
Bayesian Deconditional Kernel Mean Embeddings
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2830-2838
Faster Stochastic Alternating Direction Method of Multipliers for Nonconvex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2839-2848
Unsupervised Deep Learning by Neighbourhood Discovery
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2849-2858
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Detecting Overlapping and Correlated Communities without Pure Nodes: Identifiability and Algorithm
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2859-2868
Hierarchical Importance Weighted Autoencoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2869-2878
Stable and Fair Classification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2879-2890
Addressing the Loss-Metric Mismatch with Adaptive Loss Alignment
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2891-2900
Causal Discovery and Forecasting in Nonstationary Environments with State-Space Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2901-2910
Composing Entropic Policies using Divergence Correction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2911-2920
HexaGAN: Generative Adversarial Nets for Real World Classification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2921-2930
Overcoming Mean-Field Approximations in Recurrent Gaussian Process Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2931-2940
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Learning Structured Decision Problems with Unawareness
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2941-2950
Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2951-2960
Actor-Attention-Critic for Multi-Agent Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2961-2970
Complementary-Label Learning for Arbitrary Losses and Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2971-2980
Causal Identification under Markov Equivalence: Completeness Results
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2981-2989
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Learning from a Learner
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:2990-2999
Differentially Private Fair Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3000-3008
Sum-of-Squares Polynomial Flow
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3009-3018
DBSCAN++: Towards fast and scalable density clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3019-3029
Learning What and Where to Transfer
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3030-3039
Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3040-3049
A Deep Reinforcement Learning Perspective on Internet Congestion Control
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3050-3059
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Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3060-3070
Ladder Capsule Network
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3071-3079
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Training CNNs with Selective Allocation of Channels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3080-3090
Learning Discrete and Continuous Factors of Data via Alternating Disentanglement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3091-3099
Improved Zeroth-Order Variance Reduced Algorithms and Analysis for Nonconvex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3100-3109
Neural Logic Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3110-3119
Finding Options that Minimize Planning Time
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3120-3129
Discovering Options for Exploration by Minimizing Cover Time
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3130-3139
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Kernel Mean Matching for Content Addressability of GANs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3140-3151
GOODE: A Gaussian Off-The-Shelf Ordinary Differential Equation Solver
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3152-3162
Bilinear Bandits with Low-rank Structure
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3163-3172
Statistical Foundations of Virtual Democracy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3173-3182
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Molecular Hypergraph Grammar with Its Application to Molecular Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3183-3191
Robust Influence Maximization for Hyperparametric Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3192-3200
Classifying Treatment Responders Under Causal Effect Monotonicity
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3201-3210
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Trainable Decoding of Sets of Sequences for Neural Sequence Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3211-3221
Myopic Posterior Sampling for Adaptive Goal Oriented Design of Experiments
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3222-3232
Differentially Private Learning of Geometric Concepts
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3233-3241
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Policy Consolidation for Continual Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3242-3251
Error Feedback Fixes SignSGD and other Gradient Compression Schemes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3252-3261
Riemannian adaptive stochastic gradient algorithms on matrix manifolds
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3262-3271
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Neural Inverse Knitting: From Images to Manufacturing Instructions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3272-3281
Processing Megapixel Images with Deep Attention-Sampling Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3282-3291
Robust Estimation of Tree Structured Gaussian Graphical Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3292-3300
Shallow-Deep Networks: Understanding and Mitigating Network Overthinking
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3301-3310
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Submodular Streaming in All Its Glory: Tight Approximation, Minimum Memory and Low Adaptive Complexity
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3311-3320
Adaptive Scale-Invariant Online Algorithms for Learning Linear Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3321-3330
CHiVE: Varying Prosody in Speech Synthesis with a Linguistically Driven Dynamic Hierarchical Conditional Variational Network
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3331-3340
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Collaborative Evolutionary Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3341-3350
Geometry Aware Convolutional Filters for Omnidirectional Images Representation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3351-3359
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EMI: Exploration with Mutual Information
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3360-3369
FloWaveNet : A Generative Flow for Raw Audio
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3370-3378
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Curiosity-Bottleneck: Exploration By Distilling Task-Specific Novelty
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3379-3388
Contextual Multi-armed Bandit Algorithm for Semiparametric Reward Model
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3389-3397
Uniform Convergence Rate of the Kernel Density Estimator Adaptive to Intrinsic Volume Dimension
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3398-3407
Bit-Swap: Recursive Bits-Back Coding for Lossless Compression with Hierarchical Latent Variables
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3408-3417
CompILE: Compositional Imitation Learning and Execution
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3418-3428
Adaptive and Safe Bayesian Optimization in High Dimensions via One-Dimensional Subspaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3429-3438
AUCμ: A Performance Metric for Multi-Class Machine Learning Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3439-3447
Fair k-Center Clustering for Data Summarization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3448-3457
Guarantees for Spectral Clustering with Fairness Constraints
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3458-3467
POPQORN: Quantifying Robustness of Recurrent Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3468-3477
Decentralized Stochastic Optimization and Gossip Algorithms with Compressed Communication
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3478-3487
Robust Learning from Untrusted Sources
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3488-3498
Stochastic Beams and Where To Find Them: The Gumbel-Top-k Trick for Sampling Sequences Without Replacement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3499-3508
LIT: Learned Intermediate Representation Training for Model Compression
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3509-3518
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Similarity of Neural Network Representations Revisited
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3519-3529
On the Complexity of Approximating Wasserstein Barycenters
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3530-3540
Estimate Sequences for Variance-Reduced Stochastic Composite Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3541-3550
Faster Algorithms for Binary Matrix Factorization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3551-3559
Loss Landscapes of Regularized Linear Autoencoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3560-3569
Geometry and Symmetry in Short-and-Sparse Deconvolution
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3570-3580
A Large-Scale Study on Regularization and Normalization in GANs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3581-3590
Making Decisions that Reduce Discriminatory Impacts
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3591-3600
Garbage In, Reward Out: Bootstrapping Exploration in Multi-Armed Bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3601-3610
Characterizing Well-Behaved vs. Pathological Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3611-3621
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3622-3631
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A Recurrent Neural Cascade-based Model for Continuous-Time Diffusion
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3632-3641
Projection onto Minkowski Sums with Application to Constrained Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3642-3651
Safe Policy Improvement with Baseline Bootstrapping
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3652-3661
A Better k-means++ Algorithm via Local Search
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3662-3671
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Lorentzian Distance Learning for Hyperbolic Representations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3672-3681
DP-GP-LVM: A Bayesian Non-Parametric Model for Learning Multivariate Dependency Structures
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3682-3691
POLITEX: Regret Bounds for Policy Iteration using Expert Prediction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3692-3702
Batch Policy Learning under Constraints
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3703-3712
Target-Based Temporal-Difference Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3713-3722
Functional Transparency for Structured Data: a Game-Theoretic Approach
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3723-3733
Self-Attention Graph Pooling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3734-3743
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Set Transformer: A Framework for Attention-based Permutation-Invariant Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3744-3753
First-Order Algorithms Converge Faster than $O(1/k)$ on Convex Problems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3754-3762
Robust Inference via Generative Classifiers for Handling Noisy Labels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3763-3772
Sublinear Time Nearest Neighbor Search over Generalized Weighted Space
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3773-3781
MONK Outlier-Robust Mean Embedding Estimation by Median-of-Means
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3782-3793
Cheap Orthogonal Constraints in Neural Networks: A Simple Parametrization of the Orthogonal and Unitary Group
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3794-3803
Are Generative Classifiers More Robust to Adversarial Attacks?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3804-3814
Sublinear quantum algorithms for training linear and kernel-based classifiers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3815-3824
LGM-Net: Learning to Generate Matching Networks for Few-Shot Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3825-3834
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Graph Matching Networks for Learning the Similarity of Graph Structured Objects
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3835-3845
Area Attention
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3846-3855
Online Learning to Rank with Features
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3856-3865
NATTACK: Learning the Distributions of Adversarial Examples for an Improved Black-Box Attack on Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3866-3876
Bayesian Joint Spike-and-Slab Graphical Lasso
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3877-3885
Exploiting Worker Correlation for Label Aggregation in Crowdsourcing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3886-3895
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Adversarial camera stickers: A physical camera-based attack on deep learning systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3896-3904
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Towards a Unified Analysis of Random Fourier Features
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3905-3914
Feature-Critic Networks for Heterogeneous Domain Generalization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3915-3924
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Learn to Grow: A Continual Structure Learning Framework for Overcoming Catastrophic Forgetting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3925-3934
Alternating Minimizations Converge to Second-Order Optimal Solutions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3935-3943
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Cautious Regret Minimization: Online Optimization with Long-Term Budget Constraints
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3944-3952
Regularization in directable environments with application to Tetris
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3953-3962
Inference and Sampling of $K_33$-free Ising Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3963-3972
Kernel-Based Reinforcement Learning in Robust Markov Decision Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3973-3981
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On Efficient Optimal Transport: An Analysis of Greedy and Accelerated Mirror Descent Algorithms
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3982-3991
Fast and Simple Natural-Gradient Variational Inference with Mixture of Exponential-family Approximations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:3992-4002
Acceleration of SVRG and Katyusha X by Inexact Preconditioning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4003-4012
Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4013-4022
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Rao-Blackwellized Stochastic Gradients for Discrete Distributions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4023-4031
Sparse Extreme Multi-label Learning with Oracle Property
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4032-4041
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Data Poisoning Attacks on Stochastic Bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4042-4050
The Implicit Fairness Criterion of Unconstrained Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4051-4060
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Taming MAML: Efficient unbiased meta-reinforcement learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4061-4071
On Certifying Non-Uniform Bounds against Adversarial Attacks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4072-4081
Understanding and Accelerating Particle-Based Variational Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4082-4092
Understanding MCMC Dynamics as Flows on the Wasserstein Space
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4093-4103
Sliced-Wasserstein Flows: Nonparametric Generative Modeling via Optimal Transport and Diffusions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4104-4113
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4114-4124
Bayesian Counterfactual Risk Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4125-4133
PA-GD: On the Convergence of Perturbed Alternating Gradient Descent to Second-Order Stationary Points for Structured Nonconvex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4134-4143
Neurally-Guided Structure Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4144-4153
Optimal Algorithms for Lipschitz Bandits with Heavy-tailed Rewards
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4154-4163
CoT: Cooperative Training for Generative Modeling of Discrete Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4164-4172
Generalized Approximate Survey Propagation for High-Dimensional Estimation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4173-4182
High-Fidelity Image Generation With Fewer Labels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4183-4192
Leveraging Low-Rank Relations Between Surrogate Tasks in Structured Prediction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4193-4202
Differentiable Dynamic Normalization for Learning Deep Representation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4203-4211
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Disentangled Graph Convolutional Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4212-4221
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Variational Implicit Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4222-4233
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4234-4243
Bayesian leave-one-out cross-validation for large data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4244-4253
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4254-4263
Guided evolutionary strategies: augmenting random search with surrogate gradients
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4264-4273
Universal Multi-Party Poisoning Attacks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4274-4283
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Traditional and Heavy Tailed Self Regularization in Neural Network Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4284-4293
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Curvature-Exploiting Acceleration of Elastic Net Computations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4294-4303
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4304-4313
Calibrated Model-Based Deep Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4314-4323
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4324-4332
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4333-4342
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4343-4351
Adversarial Generation of Time-Frequency Features with application in audio synthesis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4352-4362
On the Universality of Invariant Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4363-4371
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4372-4381
Fairness-Aware Learning for Continuous Attributes and Treatments
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4382-4391
Optimal Minimal Margin Maximization with Boosting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4392-4401
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Disentangling Disentanglement in Variational Autoencoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4402-4412
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4413-4423
Distributional Reinforcement Learning for Efficient Exploration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4424-4434
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Graphical-model based estimation and inference for differential privacy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4435-4444
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4445-4455
Toward Controlling Discrimination in Online Ad Auctions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4456-4465
Stochastic Blockmodels meet Graph Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4466-4474
Imputing Missing Events in Continuous-Time Event Streams
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4475-4485
Same, Same But Different: Recovering Neural Network Quantization Error Through Weight Factorization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4486-4495
The Wasserstein Transform
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4496-4504
Ithemal: Accurate, Portable and Fast Basic Block Throughput Estimation using Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4505-4515
Geometric Losses for Distributional Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4516-4525
Spectral Clustering of Signed Graphs via Matrix Power Means
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4526-4536
Simple Stochastic Gradient Methods for Non-Smooth Non-Convex Regularized Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4537-4545
Reinforcement Learning in Configurable Continuous Environments
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4546-4555
Understanding and correcting pathologies in the training of learned optimizers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4556-4565
Optimality Implies Kernel Sum Classifiers are Statistically Efficient
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4566-4574
On Dropout and Nuclear Norm Regularization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4575-4584
Discriminative Regularization for Latent Variable Models with Applications to Electrocardiography
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4585-4594
Formal Privacy for Functional Data with Gaussian Perturbations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4595-4604
Co-manifold learning with missing data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4605-4614
Agnostic Federated Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4615-4625
Flat Metric Minimization with Applications in Generative Modeling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4626-4635
Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4636-4645
Parameter efficient training of deep convolutional neural networks by dynamic sparse reparameterization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4646-4655
A Dynamical Systems Perspective on Nesterov Acceleration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4656-4662
Relational Pooling for Graph Representations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4663-4673
Learning Optimal Fair Policies
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4674-4682
Lexicographic and Depth-Sensitive Margins in Homogeneous and Non-Homogeneous Deep Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4683-4692
A Wrapped Normal Distribution on Hyperbolic Space for Gradient-Based Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4693-4702
SGD without Replacement: Sharper Rates for General Smooth Convex Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4703-4711
Dropout as a Structured Shrinkage Prior
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4712-4722
Hybrid Models with Deep and Invertible Features
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4723-4732
Learning Context-dependent Label Permutations for Multi-label Classification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4733-4742
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Zero-Shot Knowledge Distillation in Deep Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4743-4751
A Framework for Bayesian Optimization in Embedded Subspaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4752-4761
Phaseless PCA: Low-Rank Matrix Recovery from Column-wise Phaseless Measurements
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4762-4770
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Safe Grid Search with Optimal Complexity
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4771-4780
Learning to bid in revenue-maximizing auctions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4781-4789
On Connected Sublevel Sets in Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4790-4799
Anomaly Detection With Multiple-Hypotheses Predictions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4800-4809
Non-Asymptotic Analysis of Fractional Langevin Monte Carlo for Non-Convex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4810-4819
Rotation Invariant Householder Parameterization for Bayesian PCA
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4820-4828
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Lossless or Quantized Boosting with Integer Arithmetic
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4829-4838
Training Neural Networks with Local Error Signals
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4839-4850
Remember and Forget for Experience Replay
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4851-4860
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Learning to Infer Program Sketches
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4861-4870
Tensor Variable Elimination for Plated Factor Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4871-4880
Counterfactual Off-Policy Evaluation with Gumbel-Max Structural Causal Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4881-4890
Model Function Based Conditional Gradient Method with Armijo-like Line Search
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4891-4900
TensorFuzz: Debugging Neural Networks with Coverage-Guided Fuzzing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4901-4911
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Scalable Learning in Reproducing Kernel Krein Spaces
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4912-4921
Approximation and non-parametric estimation of ResNet-type convolutional neural networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4922-4931
Orthogonal Random Forest for Causal Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4932-4941
Inferring Heterogeneous Causal Effects in Presence of Spatial Confounding
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4942-4950
Overparameterized Nonlinear Learning: Gradient Descent Takes the Shortest Path?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4951-4960
Multiplicative Weights Updates as a distributed constrained optimization algorithm: Convergence to second-order stationary points almost always
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4961-4969
Improving Adversarial Robustness via Promoting Ensemble Diversity
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4970-4979
Nonparametric Bayesian Deep Networks with Local Competition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4980-4988
Optimistic Policy Optimization via Multiple Importance Sampling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4989-4999
Deep Residual Output Layers for Neural Language Generation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5000-5011
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Measurements of Three-Level Hierarchical Structure in the Outliers in the Spectrum of Deepnet Hessians
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5012-5021
Generalized Majorization-Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5022-5031
Variational Laplace Autoencoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5032-5041
The Effect of Network Width on Stochastic Gradient Descent and Generalization: an Empirical Study
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5042-5051
Spectral Approximate Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5052-5061
Self-Supervised Exploration via Disagreement
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5062-5071
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Subspace Robust Wasserstein Distances
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5072-5081
Fingerprint Policy Optimisation for Robust Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5082-5091
COMIC: Multi-view Clustering Without Parameter Selection
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5092-5101
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Domain Agnostic Learning with Disentangled Representations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5102-5112
Collaborative Channel Pruning for Deep Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5113-5122
Exploiting structure of uncertainty for efficient matroid semi-bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5123-5132
Cognitive model priors for predicting human decisions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5133-5141
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Towards Understanding Knowledge Distillation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5142-5151
Temporal Gaussian Mixture Layer for Videos
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5152-5161
Voronoi Boundary Classification: A High-Dimensional Geometric Approach via Weighted Monte Carlo Integration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5162-5170
On Variational Bounds of Mutual Information
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5171-5180
Hiring Under Uncertainty
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5181-5189
SAGA with Arbitrary Sampling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5190-5199
SGD: General Analysis and Improved Rates
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5200-5209
AutoVC: Zero-Shot Voice Style Transfer with Only Autoencoder Loss
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5210-5219
Fault Tolerance in Iterative-Convergent Machine Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5220-5230
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech Recognition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5231-5240
GMNN: Graph Markov Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5241-5250
Nonlinear Distributional Gradient Temporal-Difference Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5251-5260
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Learning to Collaborate in Markov Decision Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5261-5270
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Meta-Learning Neural Bloom Filters
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5271-5280
Direct Uncertainty Prediction for Medical Second Opinions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5281-5290
Game Theoretic Optimization via Gradient-based Nikaido-Isoda Function
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5291-5300
On the Spectral Bias of Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5301-5310
Look Ma, No Latent Variables: Accurate Cutset Networks via Compilation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5311-5320
Does Data Augmentation Lead to Positive Margin?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5321-5330
Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5331-5340
Screening rules for Lasso with non-convex Sparse Regularizers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5341-5350
Topological Data Analysis of Decision Boundaries with Application to Model Selection
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5351-5360
HyperGAN: A Generative Model for Diverse, Performant Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5361-5369
Efficient On-Device Models using Neural Projections
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5370-5379
A Block Coordinate Descent Proximal Method for Simultaneous Filtering and Parameter Estimation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5380-5388
Do ImageNet Classifiers Generalize to ImageNet?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5389-5400
Fast Rates for a kNN Classifier Robust to Unknown Asymmetric Label Noise
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5401-5409
Almost Unsupervised Text to Speech and Automatic Speech Recognition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5410-5419
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Adaptive Antithetic Sampling for Variance Reduction
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5420-5428
Adversarial Online Learning with noise
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5429-5437
A Polynomial Time MCMC Method for Sampling from Continuous Determinantal Point Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5438-5447
A Persistent Weisfeiler-Lehman Procedure for Graph Classification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5448-5458
Efficient learning of smooth probability functions from Bernoulli tests with guarantees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5459-5467
Separating value functions across time-scales
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5468-5477
Online Convex Optimization in Adversarial Markov Decision Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5478-5486
Good Initializations of Variational Bayes for Deep Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5487-5497
The Odds are Odd: A Statistical Test for Detecting Adversarial Examples
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5498-5507
Neuron birth-death dynamics accelerates gradient descent and converges asymptotically
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5508-5517
Iterative Linearized Control: Stable Algorithms and Complexity Guarantees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5518-5527
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Statistics and Samples in Distributional Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5528-5536
A Contrastive Divergence for Combining Variational Inference and MCMC
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5537-5545
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5546-5557
White-box vs Black-box: Bayes Optimal Strategies for Membership Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5558-5567
An Optimal Private Stochastic-MAB Algorithm based on Optimal Private Stopping Rule
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5579-5588
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Deep Gaussian Processes with Importance-Weighted Variational Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5589-5598
Multivariate Submodular Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5599-5609
Near optimal finite time identification of arbitrary linear dynamical systems
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5610-5618
Breaking Inter-Layer Co-Adaptation by Classifier Anonymization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5619-5627
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A Theoretical Analysis of Contrastive Unsupervised Representation Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5628-5637
Locally Private Bayesian Inference for Count Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5638-5648
Weakly-Supervised Temporal Localization via Occurrence Count Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5649-5659
Discovering Context Effects from Raw Choice Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5660-5669
On the Feasibility of Learning, Rather than Assuming, Human Biases for Reward Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5670-5679
Exploration Conscious Reinforcement Learning Revisited
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5680-5689
Compressed Factorization: Fast and Accurate Low-Rank Factorization of Compressively-Sensed Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5690-5700
Conditional Independence in Testing Bayesian Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5701-5709
Learning to Clear the Market
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5710-5718
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Mixture Models for Diverse Machine Translation: Tricks of the Trade
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5719-5728
Hessian Aided Policy Gradient
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5729-5738
Learning with Bad Training Data via Iterative Trimmed Loss Minimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5739-5748
Replica Conditional Sequential Monte Carlo
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5749-5757
Scalable Training of Inference Networks for Gaussian-Process Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5758-5768
Fast Direct Search in an Optimally Compressed Continuous Target Space for Efficient Multi-Label Active Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5769-5778
Model-Based Active Exploration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5779-5788
Rehashing Kernel Evaluation in High Dimensions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5789-5798
Revisiting precision recall definition for generative modeling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5799-5808
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First-Order Adversarial Vulnerability of Neural Networks and Input Dimension
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5809-5817
Refined Complexity of PCA with Outliers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5818-5826
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A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5827-5837
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Non-Parametric Priors For Generative Adversarial Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5838-5847
Understanding Impacts of High-Order Loss Approximations and Features in Deep Learning Interpretation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5848-5856
kernelPSI: a Post-Selection Inference Framework for Nonlinear Variable Selection
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5857-5865
GEOMetrics: Exploiting Geometric Structure for Graph-Encoded Objects
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5866-5876
The Evolved Transformer
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5877-5886
QTRAN: Learning to Factorize with Transformation for Cooperative Multi-Agent Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5887-5896
Distribution calibration for regression
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5897-5906
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SELFIE: Refurbishing Unclean Samples for Robust Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5907-5915
Revisiting the Softmax Bellman Operator: New Benefits and New Perspective
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5916-5925
MASS: Masked Sequence to Sequence Pre-training for Language Generation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5926-5936
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Dual Entangled Polynomial Code: Three-Dimensional Coding for Distributed Matrix Multiplication
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5937-5945
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Compressing Gradient Optimizers via Count-Sketches
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5946-5955
Escaping Saddle Points with Adaptive Gradient Methods
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5956-5965
Faster Attend-Infer-Repeat with Tractable Probabilistic Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5966-5975
Insertion Transformer: Flexible Sequence Generation via Insertion Operations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5976-5985
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BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5986-5995
Learning Optimal Linear Regularizers
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:5996-6004
CAB: Continuous Adaptive Blending for Policy Evaluation and Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6005-6014
Learning Distance for Sequences by Learning a Ground Metric
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6015-6025
Contextual Memory Trees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6026-6035
Provably Efficient Imitation Learning from Observation Alone
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6036-6045
Active Learning for Decision-Making from Imbalanced Observational Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6046-6055
Robustly Disentangled Causal Mechanisms: Validating Deep Representations for Interventional Robustness
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6056-6065
Hyperbolic Disk Embeddings for Directed Acyclic Graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6066-6075
Accelerated Flow for Probability Distributions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6076-6085
Equivariant Transformer Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6086-6095
Making Deep Q-learning methods robust to time discretization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6096-6104
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6105-6114
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Hierarchical Decompositional Mixtures of Variational Autoencoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6115-6124
Mallows ranking models: maximum likelihood estimate and regeneration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6125-6134
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Correlated Variational Auto-Encoders
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6135-6144
The Variational Predictive Natural Gradient
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6145-6154
DoubleSqueeze: Parallel Stochastic Gradient Descent with Double-pass Error-Compensated Compression
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6155-6165
Adaptive Neural Trees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6166-6175
Variational Annealing of GANs: A Langevin Perspective
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6176-6185
Predicate Exchange: Inference with Declarative Knowledge
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6186-6195
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The Natural Language of Actions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6196-6205
Kernel Normalized Cut: a Theoretical Revisit
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6206-6214
Action Robust Reinforcement Learning and Applications in Continuous Control
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6215-6224
Concentration Inequalities for Conditional Value at Risk
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6225-6233
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Combating Label Noise in Deep Learning using Abstention
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6234-6243
ELF OpenGo: an analysis and open reimplementation of AlphaZero
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6244-6253
Random Matrix Improved Covariance Estimation for a Large Class of Metrics
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6254-6263
Transfer of Samples in Policy Search via Multiple Importance Sampling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6264-6274
Optimal Transport for structured data with application on graphs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6275-6284
Discovering Latent Covariance Structures for Multiple Time Series
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6285-6294
Bayesian Generative Active Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6295-6304
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DeepNose: Using artificial neural networks to represent the space of odorants
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6305-6314
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LR-GLM: High-Dimensional Bayesian Inference Using Low-Rank Data Approximations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6315-6324
Learning Hawkes Processes Under Synchronization Noise
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6325-6334
Homomorphic Sensing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6335-6344
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Metropolis-Hastings Generative Adversarial Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6345-6353
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Distributed, Egocentric Representations of Graphs for Detecting Critical Structures
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6354-6362
Sublinear Space Private Algorithms Under the Sliding Window Model
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6363-6372
Fairness without Harm: Decoupled Classifiers with Preference Guarantees
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6373-6382
Large-Scale Sparse Kernel Canonical Correlation Analysis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6383-6391
Characterization of Convex Objective Functions and Optimal Expected Convergence Rates for SGD
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6392-6400
Composing Value Functions in Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6401-6409
Model Comparison for Semantic Grouping
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6410-6417
Learning Dependency Structures for Weak Supervision Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6418-6427
Probabilistic Neural Symbolic Models for Interpretable Visual Question Answering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6428-6437
Manifold Mixup: Better Representations by Interpolating Hidden States
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6438-6447
Maximum Likelihood Estimation for Learning Populations of Parameters
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6448-6457
Understanding Priors in Bayesian Neural Networks at the Unit Level
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6458-6467
On the Design of Estimators for Bandit Off-Policy Evaluation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6468-6476
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Learning to select for a predefined ranking
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6477-6486
On the Limitations of Representing Functions on Sets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6487-6494
Graph Convolutional Gaussian Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6495-6504
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Gaining Free or Low-Cost Interpretability with Interpretable Partial Substitute
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6505-6514
Convolutional Poisson Gamma Belief Network
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6515-6525
Differentially Private Empirical Risk Minimization with Non-convex Loss Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6526-6535
Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6536-6544
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SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6545-6554
Improving Neural Language Modeling via Adversarial Training
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6555-6565
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EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6566-6575
Nonlinear Stein Variational Gradient Descent for Learning Diversified Mixture Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6576-6585
On the Convergence and Robustness of Adversarial Training
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6586-6595
State-Regularized Recurrent Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6596-6606
Deep Factors for Forecasting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6607-6617
Repairing without Retraining: Avoiding Disparate Impact with Counterfactual Distributions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6618-6627
On Sparse Linear Regression in the Local Differential Privacy Model
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6628-6637
Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6638-6647
On the Generalization Gap in Reparameterizable Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6648-6658
Bias Also Matters: Bias Attribution for Deep Neural Network Explanation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6659-6667
Jumpout : Improved Dropout for Deep Neural Networks with ReLUs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6668-6676
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AdaGrad Stepsizes: Sharp Convergence Over Nonconvex Landscapes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6677-6686
Generalized Linear Rule Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6687-6696
On the statistical rate of nonlinear recovery in generative models with heavy-tailed data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6697-6706
CapsAndRuns: An Improved Method for Approximately Optimal Algorithm Configuration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6707-6715
Non-Monotonic Sequential Text Generation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6716-6726
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6727-6736
Learning deep kernels for exponential family densities
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6737-6746
Improving Model Selection by Employing the Test Data
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6747-6756
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Automatic Classifiers as Scientific Instruments: One Step Further Away from Ground-Truth
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6757-6765
Moment-Based Variational Inference for Markov Jump Processes
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6766-6775
End-to-End Probabilistic Inference for Nonstationary Audio Analysis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6776-6785
Fairness risk measures
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6786-6797
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6798-6807
Wasserstein Adversarial Examples via Projected Sinkhorn Iterations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6808-6817
Imitation Learning from Imperfect Demonstration
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6818-6827
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6828-6839
Heterogeneous Model Reuse via Optimizing Multiparty Multiclass Margin
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6840-6849
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Deep Compressed Sensing
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6850-6860
Simplifying Graph Convolutional Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6861-6871
Domain Adaptation with Asymmetrically-Relaxed Distribution Alignment
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6872-6881
On Scalable and Efficient Computation of Large Scale Optimal Transport
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6882-6892
Zeno: Distributed Stochastic Gradient Descent with Suspicion-based Fault-tolerance
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6893-6901
Differentiable Linearized ADMM
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6902-6911
Calibrated Approximate Bayesian Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6912-6920
Power k-Means Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6921-6931
Gromov-Wasserstein Learning for Graph Matching and Node Embedding
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6932-6941
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6942-6951
Learning a Prior over Intent via Meta-Inverse Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6952-6962
Variational Russian Roulette for Deep Bayesian Nonparametrics
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6963-6972
Supervised Hierarchical Clustering with Exponential Linkage
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6973-6983
Learning to Prove Theorems via Interacting with Proof Assistants
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6984-6994
Sample-Optimal Parametric Q-Learning Using Linearly Additive Features
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:6995-7004
LegoNet: Efficient Convolutional Neural Networks with Lego Filters
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7005-7014
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SWALP : Stochastic Weight Averaging in Low Precision Training
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7015-7024
ME-Net: Towards Effective Adversarial Robustness with Matrix Estimation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7025-7034
Efficient Nonconvex Regularized Tensor Completion with Structure-aware Proximal Iterations
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7035-7044
Hierarchically Structured Meta-learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7045-7054
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7055-7063
Understanding Geometry of Encoder-Decoder CNNs
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7064-7073
Defending Against Saddle Point Attack in Byzantine-Robust Distributed Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7074-7084
Rademacher Complexity for Adversarially Robust Generalization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7085-7094
ARSM: Augment-REINFORCE-Swap-Merge Estimator for Gradient Backpropagation Through Categorical Variables
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7095-7104
NAS-Bench-101: Towards Reproducible Neural Architecture Search
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7105-7114
TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7115-7123
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7124-7133
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Position-aware Graph Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7134-7143
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Learning Neurosymbolic Generative Models via Program Synthesis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7144-7153
DAG-GNN: DAG Structure Learning with Graph Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7154-7163
How does Disagreement Help Generalization against Label Corruption?
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7164-7173
On the Computation and Communication Complexity of Parallel SGD with Dynamic Batch Sizes for Stochastic Non-Convex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7174-7183
On the Linear Speedup Analysis of Communication Efficient Momentum SGD for Distributed Non-Convex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7184-7193
Multi-Agent Adversarial Inverse Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7194-7201
Distributed Learning over Unreliable Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7202-7212
Online Adaptive Principal Component Analysis and Its extensions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7213-7221
Generative Modeling of Infinite Occluded Objects for Compositional Scene Representation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7222-7231
Differential Inclusions for Modeling Nonsmooth ADMM Variants: A Continuous Limit Theory
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7232-7241
Trimming the $\ell_1$ Regularizer: Statistical Analysis, Optimization, and Applications to Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7242-7251
Bayesian Nonparametric Federated Learning of Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7252-7261
Dirichlet Simplex Nest and Geometric Inference
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7262-7271
A Conditional-Gradient-Based Augmented Lagrangian Framework
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7272-7281
Conditional Gradient Methods via Stochastic Path-Integrated Differential Estimator
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7282-7291
Context-Aware Zero-Shot Learning for Object Recognition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7292-7303
Tighter Problem-Dependent Regret Bounds in Reinforcement Learning without Domain Knowledge using Value Function Bounds
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7304-7312
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Global Convergence of Block Coordinate Descent in Deep Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7313-7323
Making Convolutional Networks Shift-Invariant Again
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7324-7334
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Warm-starting Contextual Bandits: Robustly Combining Supervised and Bandit Feedback
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7335-7344
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When Samples Are Strategically Selected
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7345-7353
Self-Attention Generative Adversarial Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7354-7363
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Circuit-GNN: Graph Neural Networks for Distributed Circuit Design
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7364-7373
LatentGNN: Learning Efficient Non-local Relations for Visual Recognition
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7374-7383
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Neural Collaborative Subspace Clustering
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7384-7393
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Incremental Randomized Sketching for Online Kernel Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7394-7403
Bridging Theory and Algorithm for Domain Adaptation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7404-7413
Adaptive Regret of Convex and Smooth Functions
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7414-7423
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Random Function Priors for Correlation Modeling
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7424-7433
Co-Representation Network for Generalized Zero-Shot Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7434-7443
SOLAR: Deep Structured Representations for Model-Based Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7444-7453
A Composite Randomized Incremental Gradient Method
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7454-7462
Fast and Stable Maximum Likelihood Estimation for Incomplete Multinomial Models
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7463-7471
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Theoretically Principled Trade-off between Robustness and Accuracy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7472-7482
Learning Novel Policies For Tasks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7483-7492
Greedy Orthogonal Pivoting Algorithm for Non-Negative Matrix Factorization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7493-7501
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Interpreting Adversarially Trained Convolutional Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7502-7511
Adaptive Monte Carlo Multiple Testing via Multi-Armed Bandits
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7512-7522
On Learning Invariant Representations for Domain Adaptation
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7523-7532
Metric-Optimized Example Weights
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7533-7542
Improving Neural Network Quantization without Retraining using Outlier Channel Splitting
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7543-7552
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Maximum Entropy-Regularized Multi-Goal Reinforcement Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7553-7562
Stochastic Iterative Hard Thresholding for Graph-structured Sparsity Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7563-7573
Lower Bounds for Smooth Nonconvex Finite-Sum Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7574-7583
Lipschitz Generative Adversarial Nets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7584-7593
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Toward Understanding the Importance of Noise in Training Neural Networks
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7594-7602
BayesNAS: A Bayesian Approach for Neural Architecture Search
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7603-7613
Transferable Clean-Label Poisoning Attacks on Deep Neural Nets
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7614-7623
Improved Dynamic Graph Learning through Fault-Tolerant Sparsification
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7624-7633
Poission Subsampled Rényi Differential Privacy
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7634-7642
Learning Classifiers for Target Domain with Limited or No Labels
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7643-7653
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The Anisotropic Noise in Stochastic Gradient Descent: Its Behavior of Escaping from Sharp Minima and Regularization Effects
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7654-7663
Surrogate Losses for Online Learning of Stepsizes in Stochastic Non-Convex Optimization
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7664-7672
Latent Normalizing Flows for Discrete Sequences
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7673-7682
Beating Stochastic and Adversarial Semi-bandits Optimally and Simultaneously
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7683-7692
Fast Context Adaptation via Meta-Learning
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7693-7702
Natural Analysts in Adaptive Data Analysis
; Proceedings of the 36th International Conference on Machine Learning, PMLR 97:7703-7711
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