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David P. Woodruff
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Publications
- 2022
- [c224]Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, Honghao Lin, David P. Woodruff:
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. ICML 2022: 3879-3900 - [c211]Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff:
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. SODA 2022: 3043-3068 - [c210]Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff:
Low-rank approximation with 1/ε1/3 matrix-vector products. STOC 2022: 1130-1143 - [i179]Ainesh Bakshi, Kenneth L. Clarkson, David P. Woodruff:
Low-Rank Approximation with 1/ε1/3 Matrix-Vector Products. CoRR abs/2202.05120 (2022) - 2021
- [i144]Nadiia Chepurko, Kenneth L. Clarkson, Praneeth Kacham, David P. Woodruff:
Near-Optimal Algorithms for Linear Algebra in the Current Matrix Multiplication Time. CoRR abs/2107.08090 (2021) - 2020
- [i121]Nadiia Chepurko, Kenneth L. Clarkson, Lior Horesh, David P. Woodruff:
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra. CoRR abs/2011.04125 (2020) - 2019
- [c150]Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff:
Dimensionality Reduction for Tukey Regression. ICML 2019: 1262-1271 - [i110]Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff:
Dimensionality Reduction for Tukey Regression. CoRR abs/1905.05376 (2019) - 2017
- [j21]Haim Avron
, Kenneth L. Clarkson, David P. Woodruff:
Faster Kernel Ridge Regression Using Sketching and Preconditioning. SIAM J. Matrix Anal. Appl. 38(4): 1116-1138 (2017) - [c115]Haim Avron
, Kenneth L. Clarkson, David P. Woodruff:
Sharper Bounds for Regularized Data Fitting. APPROX-RANDOM 2017: 27:1-27:22 - [c103]Kenneth L. Clarkson, David P. Woodruff:
Low-Rank PSD Approximation in Input-Sparsity Time. SODA 2017: 2061-2072 - 2016
- [j17]Kenneth L. Clarkson, Petros Drineas
, Malik Magdon-Ismail, Michael W. Mahoney, Xiangrui Meng, David P. Woodruff:
The Fast Cauchy Transform and Faster Robust Linear Regression. SIAM J. Comput. 45(3): 763-810 (2016) - [i47]Haim Avron, Kenneth L. Clarkson, David P. Woodruff:
Faster Kernel Ridge Regression Using Sketching and Preconditioning. CoRR abs/1611.03220 (2016) - [i46]Haim Avron, Kenneth L. Clarkson, David P. Woodruff:
Sharper Bounds for Regression and Low-Rank Approximation with Regularization. CoRR abs/1611.03225 (2016) - 2015
- [c80]Kenneth L. Clarkson, David P. Woodruff:
Input Sparsity and Hardness for Robust Subspace Approximation. FOCS 2015: 310-329 - [c76]Kenneth L. Clarkson, David P. Woodruff:
Sketching for M-Estimators: A Unified Approach to Robust Regression. SODA 2015: 921-939 - [i37]Kenneth L. Clarkson, David P. Woodruff:
Input Sparsity and Hardness for Robust Subspace Approximation. CoRR abs/1510.06073 (2015) - 2013
- [c58]Kenneth L. Clarkson, Petros Drineas
, Malik Magdon-Ismail, Michael W. Mahoney, Xiangrui Meng, David P. Woodruff:
The Fast Cauchy Transform and Faster Robust Linear Regression. SODA 2013: 466-477 - [c55]Kenneth L. Clarkson, David P. Woodruff:
Low rank approximation and regression in input sparsity time. STOC 2013: 81-90 - 2012
- [j7]Kenneth L. Clarkson, Elad Hazan
, David P. Woodruff:
Sublinear optimization for machine learning. J. ACM 59(5): 23:1-23:49 (2012) - [i22]Kenneth L. Clarkson, Petros Drineas, Malik Magdon-Ismail, Michael W. Mahoney, Xiangrui Meng, David P. Woodruff:
The Fast Cauchy Transform: with Applications to Basis Construction, Regression, and Subspace Approximation in L1. CoRR abs/1207.4684 (2012) - [i21]Kenneth L. Clarkson, David P. Woodruff:
Low Rank Approximation and Regression in Input Sparsity Time. CoRR abs/1207.6365 (2012) - 2010
- [c31]Kenneth L. Clarkson, Elad Hazan
, David P. Woodruff:
Sublinear Optimization for Machine Learning. FOCS 2010: 449-457 - [i13]Kenneth L. Clarkson, Elad Hazan, David P. Woodruff:
Sublinear Optimization for Machine Learning. CoRR abs/1010.4408 (2010) - 2009
- [c19]Kenneth L. Clarkson, David P. Woodruff:
Numerical linear algebra in the streaming model. STOC 2009: 205-214

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