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ORCID24th SDM 2024: Houston, TX, USA
- Shashi Shekhar, Vagelis Papalexakis, Jing Gao, Zhe Jiang, Matteo Riondato:
Proceedings of the 2024 SIAM International Conference on Data Mining, SDM 2024, Houston, TX, USA, April 18-20, 2024. SIAM 2024, ISBN 978-1-61197-803-2 - Karuna Bhaila, Wen Huang, Yongkai Wu
, Xintao Wu:
Local Differential Privacy in Graph Neural Networks: a Reconstruction Approach. 1-9 - Chuxuan Hu, Qinghai Zhou, Hanghang Tong:
Genius: Subteam Replacement with Clustering-based Graph Neural Networks. 10-18 - Yewen Wang, Shichang Zhang, John (Junghoo) Cho, Yizhou Sun:
Laplacian Score Benefit Adaptive Filter Selection for Graph Neural Networks. 19-27 - Zheng Zhang, Liang Zhao:
Self-Similar Graph Neural Network for Hierarchical Graph Learning. 28-36 - Audrey Der, Chin-Chia Michael Yeh, Yan Zheng, Junpeng Wang, Zhongfang Zhuang, Liang Wang, Wei Zhang, Eamonn J. Keogh:
PUPAE: Intuitive and Actionable Explanations for Time Series Anomalies. 37-45 - Ian Davidson, Michael J. Livanos, Antoine Gourru, Peter B. Walker, Julien Velcin, S. S. Ravi:
An Exemplars-Based Approach for Explainable Clustering: Complexity and Efficient Approximation Algorithms. 46-54 - Michal K. Grzeszczyk, Tomasz Trzcinski, Arkadiusz Sitek:
MISS: Multiclass Interpretable Scoring Systems. 55-63 - Ryoji Kubo, Djellel Eddine Difallah:
XGExplainer: Robust Evaluation-based Explanation for Graph Neural Networks. 64-72 - Dazhou Yu, Binbin Chen, Yun Li, Suman Dhakal, Yifei Zhang, Zhenke Liu, Minxing Zhang, Jie Zhang, Liang Zhao:
STES: A Spatiotemporal Explanation Supervision Framework. 73-81 - Dongyu Zhang, Ruofan Hu, Elke A. Rundensteiner:
CoLafier: Collaborative Noisy Label Purifier With Local Intrinsic Dimensionality Guidance. 82-90 - Mahsa Forouzesh, Patrick Thiran:
Differences Between Hard and Noisy-labeled Samples: An Empirical Study. 91-99 - Saket Sathe, Charu Aggarwal, Horst Samulowitz, Deepak S. Turaga:
Feature-Engineered Random Forests. 100-108 - Dzung T. Phan, Lam M. Nguyen, Jayant Kalagnanam, Chandra Reddy:
Multi-polytope Machine for Classification. 109-117 - Shuo Meng, Xinshuo Liang, Shuai Zhang, Leqi Lei, Hanbai Wu, Saira Iqbal, Jinlian Hu:
YOLO-OCR: End-to-end Compound Figure Separation and Label Recognition of Images in Scientific Publications. 118-126 - Maolin Wang, Yaoming Zhen, Yu Pan, Yao Zhao, Chenyi Zhuang, Zenglin Xu, Ruocheng Guo, Xiangyu Zhao:
Tensorized Hypergraph Neural Networks. 127-135 - Xueqi Ma, Xingjun Ma, Sarah M. Erfani, James Bailey:
Training Sparse Graph Neural Networks via Pruning and Sprouting. 136-144 - Kun Peng, Lei Jiang, Hao Peng, Rui Liu, Zhengtao Yu, Jiaqian Ren, Zhifeng Hao, Philip S. Yu:
Prompt Based Tri-Channel Graph Convolution Neural Network for Aspect Sentiment Triplet Extraction. 145-153 - Zheng Zhang, Sirui Li, Jingcheng Zhou, Junxiang Wang, Abhinav Angirekula, Allen Zhang, Liang Zhao:
Non-Euclidean Spatial Graph Neural Network. 154-162 - Weijieying Ren, Vasant G. Honavar:
EsaCL: An Efficient Continual Learning Algorithm. 163-171 - Frederik Brüning, Anne Driemel, Alperen Ergür, Heiko Röglin:
On the number of iterations of the DBA algorithm. 172-180 - Zhong Chen, Yi He, Di Wu, Huixin Zhan, Victor S. Sheng, Kun Zhang:
Robust Sparse Online Learning for Data Streams with Streaming Features. 181-189 - Giulia Bernardini, Huiping Chen, Alessio Conte, Roberto Grossi, Veronica Guerrini, Grigorios Loukides, Nadia Pisanti, Solon P. Pissis:
Utility-Oriented String Mining. 190-198 - Nevo Itzhak, Szymon Jaroszewicz, Robert Moskovitch:
Early Multiple Temporal Patterns Based Event Prediction in Heterogeneous Multivariate Temporal Data. 199-207 - Guangjie Zeng, Hao Peng, Angsheng Li, Zhiwei Liu, Runze Yang, Chunyang Liu, Lifang He:
Semi-Supervised Clustering via Structural Entropy with Different Constraints. 208-216 - Duc Toan Nguyen, Eric C. Chi:
Towards Tuning-Free Minimum-Volume Nonnegative Matrix Factorization. 217-225 - Hongchang Gao, Yubin Duan, Yihan Zhang, Jie Wu:
Decentralized Stochastic Compositional Gradient Descent for AUPRC Maximization. 226-234 - Xu Wang, Jiawei Huang, Qingyuan Yang, Jinpeng Zhang:
On Robust Wasserstein Barycenter: The Model and Algorithm. 235-243 - Wang Lu, Jindong Wang, Yidong Wang, Xing Xie:
Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution. 244-252 - Junruo Gao, Chen Ling, Carl Yang, Liang Zhao:
Helper Recommendation with seniority control in Online Health Community. 253-261 - Hongliang Chi, Cong Qi, Suhang Wang, Yao Ma:
Active Learning for Graphs with Noisy Structures. 262-270 - Houquan Zhou, Shenghua Liu, Huawei Shen, Xueqi Cheng:
Graph Summarization for Preserving Spectral Characteristics. 271-279 - Vivek Anand, Jiaming Cui, Jack Heavey, Anil Vullikanti, B. Aditya Prakash:
H2ABM: Heterogeneous Agent-based Model on Hypergraphs to Capture Group Interactions. 280-288 - Ziqiang Cui, Xing Tang, Yang Qiao, Bowei He, Liang Chen, Xiuqiang He, Chen Ma:
Treatment-Aware Hyperbolic Representation Learning for Causal Effect Estimation with Social Networks. 289-297 - Shamima Hossain, Christos Faloutsos, Boris Baer, Hyoseung Kim, Vassilis J. Tsotras:
EBV: Electronic Bee-Veterinarian for Principled Mining and Forecasting of Honeybee Time Series. 298-306 - Shaoming Xu, Ankush Khandelwal, Arvind Renganathan, Vipin Kumar:
Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling. 307-315 - Louis Carpentier, Len Feremans, Wannes Meert, Mathias Verbeke:
Pattern-based Time Series Semantic Segmentation with Gradual State Transitions. 316-324 - Yuansan Liu, Sudanthi N. R. Wijewickrema, Ang Li, Christofer Bester, Stephen J. O'Leary, James Bailey:
Time-Transformer: Integrating Local and Global Features for Better Time Series Generation. 325-333 - Rahul Ghosh, Arvind Renganathan, Wallace McAliley, Michael S. Steinbach, Christopher J. Duffy, Vipin Kumar:
Towards Entity-Aware Conditional Variational Inference for Heterogeneous Time-Series Prediction: An application to Hydrology. 334-342 - Zhao Xu, Yaochen Xie, Youzhi Luo, Xuan Zhang, Xinyi Xu, Meng Liu, Kaleb Dickerson, Cheng Deng, Maho Nakata, Shuiwang Ji:
3D Molecular Geometry Analysis with 2D Graphs. 343-351 - Lisha Ye, Jianfeng Zhou, Zhe Yin, Kunpeng Han, Haoyuan Hu, Dongjin Song:
A Novel Hybrid Graph Learning Method for Inbound Parcel Volume Forecasting in Logistics System. 352-360 - Suhan Cui, Jiaqi Wang, Yuan Zhong, Han Liu, Ting Wang, Fenglong Ma:
Automated Fusion of Multimodal Electronic Health Records for Better Medical Predictions. 361-369 - Xuanming Hu, Wei Fan, Dongjie Wang, Pengyang Wang, Yong Li, Yanjie Fu:
Dual-stage Flows-based Generative Modeling for Traceable Urban Planning. 370-378 - Jinze Wu, Haotian Zhang, Zhenya Huang, Liang Ding, Qi Liu, Jing Sha, Enhong Chen, Shijin Wang:
Graph-based Student Knowledge Profile for Online Intelligent Education. 379-387 - Michael Muller:
Data Silences: How to Unsilence the Uncertainties in Data Science. 388-391 - Zhe Jiang, Yu Wang, Zelin Xu:
Foundation Models for Spatiotemporal Tasks in the Physical World. 392-395 - Dainis Boumber, Rakesh M. Verma, Fatima Zahra Qachfar:
Blue Sky: Multilingual, Multimodal Domain Independent Deception Detection. 396-399 - Bo Yuan, Yulin Chen, Zhen Tan, Jinyan Wang, Huan Liu, Yin Zhang:
Label Distribution Learning-Enhanced Dual-KNN for Text Classification. 400-408 - Jian Yang, Xinyu Hu, Yulong Shen, Gang Xiao:
Refining Pre-trained Language Models for Domain Adaptation with Entity-Aware Discriminative and Contrastive Learning. 409-417 - Yu Cheng, Yunzhu Pan, Jiaqi Zhang, Yongxin Ni, Aixin Sun, Fajie Yuan:
An Image Dataset for Benchmarking Recommender Systems with Raw Pixels. 418-426 - Bohan Jiang, Zhen Tan, Ayushi Nirmal, Huan Liu:
Disinformation Detection: An Evolving Challenge in the Age of LLMs. 427-435 - Ujun Jeong, Ayushi Nirmal, Kritshekhar Jha, Xu Tang, H. Russell Bernard, Huan Liu:
User Migration across Multiple Social Media Platforms. 436-444 - Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar:
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. 445-453 - Liang Wang, Hao Fu, Shu Wu, Qiang Liu, Xuelei Tan, Fangsheng Huang, Mengdi Zhang, Wei Wu:
CAMLO: Cross-Attentive Multi-View Network for Long-Term Origin-Destination Flow Prediction. 454-462 - Changlu Chen, Yanbin Liu, Ling Chen, Chengqi Zhang:
Test-Time Training for Spatial-Temporal Forecasting. 463-471 - Wei Hu, Bowen Jin, Minhao Jiang, Sizhe Zhou, Zhaonan Wang, Jiawei Han, Shaowen Wang:
Geospatial Topological Relation Extraction from Text with Knowledge Augmentation. 472-480 - Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo:
Only Attending What Matter within Trajectories - Memory-Efficient Trajectory Attention. 481-489 - Cong Fu, Xuan Zhang, Huixin Zhang, Hongyi Ling, Shenglong Xu, Shuiwang Ji:
Lattice Convolutional Networks for Learning Ground States of Quantum Many-Body Systems. 490-498 - Yuan Zhong, Suhan Cui, Jiaqi Wang, Xiaochen Wang, Ziyi Yin, Yaqing Wang, Houping Xiao, Mengdi Huai, Ting Wang, Fenglong Ma:
MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation. 499-507 - Donglin Zhan, Yusheng Dai, Yiwei Dong, Jinghai He, Zhenyi Wang, James Anderson:
Meta-Adaptive Stock Movement Prediction with Two-Stage Representation Learning. 508-516 - Yuting Ma, Shuo Yu, Yanming Shen:
Pretraining Molecules with Explicit Substructure Information. 517-525 - Kunpeng Xu, Lifei Chen, Jean-Marc Patenaude, Shengrui Wang:
RHINE: A Regime-Switching Model with Nonlinear Representation for Discovering and Forecasting Regimes in Financial Markets. 526-534 - Hongyu Zhang, Dongyi Zheng, Xu Yang, Jiyuan Feng, Qing Liao:
FedDCSR: Federated Cross-domain Sequential Recommendation via Disentangled Representation Learning. 535-543 - Xinyu Zhang, Beibei Li, Beihong Jin:
Denoising Long- and Short-term Interests for Sequential Recommendation. 544-552 - Fengxin Li, Hongyan Liu, Jun He, Xiaoyong Du:
CausalCDR: Causal Embedding Learning for Cross-domain Recommendation. 553-561 - Mingjun Zhao, Liyao Jiang, Yakun Yu, Xinmin Wang, Yi Yuan, Zheng Wei, Di Niu:
DimReg: Embedding Dimension Search via Regularization for Recommender Systems. 562-570 - Zhiqiang Guo, Guohui Li, Jianjun Li, Chaoyang Wang, Si Shi:
DualVAE: Dual Disentangled Variational AutoEncoder for Recommendation. 571-579 - Tianqi Sun, Hongrui Guo, Zihan Zhang, Hongzhi Liu, Zhonghai Wu:
Exploiting Multifaceted Nature of Items and Users for Session-based Recommendation. 580-588 - Somya Sharma Chatterjee, Kelly Lindsay, Neel Chatterjee, Rohan Patil, Ilkay Altintas De Callafon, Michael S. Steinbach, Daniel Giron, Mai H. Nguyen, Vipin Kumar:
Prescribed Fire Modeling using Knowledge-Guided Machine Learning for Land Management. 589-597 - Nasrin Kalanat, Yiqun Xie, Yanhua Li, Xiaowei Jia:
Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction. 598-606 - Shreya Ghosh, Prasenjit Mitra:
Bridging Semantics: Mobility Analytics Framework for Knowledge Transfer. 607-615 - Majid Farhadloo, Arun Sharma, Jayant Gupta, Alexey A. Leontovich, Svetomir N. Markovic, Shashi Shekhar:
Towards Spatially-Lucid AI Classification in Non-Euclidean Space: An Application for MxIF Oncology Data. 616-624 - Haowen Lin, Yao-Yi Chiang, Li Xiong, Cyrus Shahabi:
Unified Modeling and Clustering of Mobility Trajectories with Spatiotemporal Point Processes. 625-633 - Dongliang Guo, Yun Fu, Sheng Li:
Ada-VAD: Domain Adaptable Video Anomaly Detection. 634-642 - Magesh Rajasekaran, Md Saiful Islam Sajol, Frej Berglind, Supratik Mukhopadhyay, Kamalika Das:
COMBOOD: A Semiparametric Approach for Detecting Out-of-distribution Data for Image Classification. 643-651 - Alastair Anderberg, James Bailey, Ricardo J. G. B. Campello, Michael E. Houle, Henrique O. Marques, Milos Radovanovic, Arthur Zimek:
Dimensionality-Aware Outlier Detection. 652-660 - Ziqi Yuan, Qingyun Sun, Haoyi Zhou, Zukun Zhu, Jianxin Li:
MultiNetAD: Multiplex Network-Based Anomaly Access Detection Featuring Semantic Hierarchies. 661-669 - Luca Stradiotti, Lorenzo Perini, Jesse Davis:
Semi-Supervised Isolation Forest for Anomaly Detection. 670-678 - Jiawei Yao, Juhua Hu:
Dual-disentangled Deep Multiple Clustering. 679-687 - Zhenzhen Chu, Jiayu Chen, Cen Chen, Chengyu Wang, Ziheng Wu, Jun Huang, Weining Qian:
DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion. 688-696 - Michael J. Livanos, Ian Davidson:
Identification and Uses of Deep Learning Backbones via Pattern Mining. 697-705 - Zhiyu Zhu, Huaming Chen, Xinyi Wang, Jiayu Zhang, Zhibo Jin, Kim-Kwang Raymond Choo, Jun Shen, Dong Yuan:
GE-AdvGAN: Improving the transferability of adversarial samples by gradient editing-based adversarial generative model. 706-714 - Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia:
Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features. 715-723 - Meng Yuan, Fuwei Zhang, Yiqi Tong, Yuxin Ying, Fuzhen Zhuang, Deqing Wang, Baoxing Huai, Yi Zhang, Jia Su:
Light POI-Guided Conversational Recommender System based on Adaptive Space. 724-733 - Qingfeng Li, Huifang Ma, Wangyu Jin, Yugang Ji, Zhixin Li:
Multi-Interest Network with Simple Diffusion for Multi-Behavior Sequential Recommendation. 734-742 - Juntao Tan, Shelby Heinecke, Zhiwei Liu, Yongjun Chen, Yongfeng Zhang, Huan Wang:
Towards More Robust and Accurate Sequential Recommendation with Cascade-guided Adversarial Training. 743-751 - Wei Yang, Haoran Zhang, Li Zhang:
Variational Invariant Representation Learning for Multimodal Recommendation. 752-760 - Ajay Krishna Vajjala, Dipak Falgun Meher, Shrunal Pothagoni, Ziwei Zhu, David S. Rosenblum:
Vietoris-Rips Complex: A New Direction for Cross-Domain Cold-Start Recommendation. 761-769 - Qiang Li, Yiqiao Sun, Linsey Pang, Liang Sun, Qingsong Wen:
Stable Synthetic Control with Anomaly Detection for Causal Inference. 770-778 - Shaofei Shen, Chenhao Zhang, Alina Bialkowski, Weitong Chen, Miao Xu:
CaMU: Disentangling Causal Effects in Deep Model Unlearning. 779-787 - Quang-Duy Tran, Bao Duong, Phuoc Nguyen, Thin Nguyen:
Robust Estimation of Causal Heteroscedastic Noise Models. 788-796 - Uday Singh Saini, Zhongfang Zhuang, Chin-Chia Michael Yeh, Wei Zhang, Evangelos E. Papalexakis:
Analysis of Causal and Non-Causal Convolution Networks for Time Series Classification. 797-805 - Ke Zhang, Lichao Sun, Bolin Ding, Siu Ming Yiu, Carl Yang:
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning. 806-814 - Reda Khoufache, Mustapha Lebbah, Hanene Azzag, Étienne Goffinet, Djamel Bouchaffra:
Distributed Collapsed Gibbs Sampler for Dirichlet Process Mixture Models in Federated Learning. 815-823 - Qikai Lu, Di Niu, Mohammadamin Samadi Khoshkho, Baochun Li:
HyperFLoRA: Federated Learning with Instantaneous Personalization. 824-832 - Ji Liu, Tianshi Che, Yang Zhou, Ruoming Jin, Huaiyu Dai, Dejing Dou, Patrick Valduriez:
AEDFL: Efficient Asynchronous Decentralized Federated Learning with Heterogeneous Devices. 833-841 - Anna Vettoruzzo, Mohamed-Rafik Bouguelia, Thorsteinn S. Rögnvaldsson:
Personalized Federated Learning with Contextual Modulation and Meta-Learning. 842-850 - Tiandi Ye, Cen Chen, Yinggui Wang, Xiang Li, Ming Gao:
UPFL: Unsupervised Personalized Federated Learning towards New Clients. 851-859 - Xuehan Zhao, Jiaqi Liu, Zhiwen Yu, Bin Guo:
HADT: Human-AI Diagnostic Team via Hierarchical Reinforcement Learning. 860-868 - Niklas Strauß, Matthias Schubert:
Spatial-Aware Deep Reinforcement Learning for the Traveling Officer Problem. 869-877 - Ehtesamul Azim, Dongjie Wang, Kunpeng Liu, Wei Zhang, Yanjie Fu:
Feature Interaction Aware Automated Data Representation Transformation. 878-886 - Runhui Wang, Luyang Kong, Yefan Tao, Andrew Borthwick, Davor Golac, Henrik Johnson, Shadie Hijazi, Dong Deng, Yongfeng Zhang:
Neural Locality Sensitive Hashing for Entity Blocking. 887-895 - Shaogang Ren, Dingcheng Li, Ping Li:
Word Embedding with Neural Probabilistic Prior. 896-904
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