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David P. Woodruff

Carnegie Mellon University

Hutch++: Optimal Stochastic Trace Estimation

Oct 21, 2020
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff

* To appears in SIAM Symposium on Simplicity in Algorithms (SOSA21) 

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WOR and $p$'s: Sketches for $\ell_p$-Sampling Without Replacement

Aug 15, 2020
Edith Cohen, Rasmus Pagh, David P. Woodruff

* 21 pages. Added references in related work in the introduction 

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Optimal $\ell_1$ Column Subset Selection and a Fast PTAS for Low Rank Approximation

Jul 20, 2020
Arvind V. Mahankali, David P. Woodruff


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On Learned Sketches for Randomized Numerical Linear Algebra

Jul 20, 2020
Simin Liu, Tianrui Liu, Ali Vakilian, Yulin Wan, David P. Woodruff

* 43 pages, 13 tables 

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Streaming Complexity of SVMs

Jul 07, 2020
Alexandr Andoni, Collin Burns, Yi Li, Sepideh Mahabadi, David P. Woodruff

* APPROX 2020 

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Vector-Matrix-Vector Queries for Solving Linear Algebra, Statistics, and Graph Problems

Jun 24, 2020
Cyrus Rashtchian, David P. Woodruff, Hanlin Zhu

* 26 pages, to be published in RANDOM 2020 

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Approximation Algorithms for Sparse Principal Component Analysis

Jun 23, 2020
Agniva Chowdhury, Petros Drineas, David P. Woodruff, Samson Zhou


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Non-Adaptive Adaptive Sampling on Turnstile Streams

Apr 23, 2020
Sepideh Mahabadi, Ilya Razenshteyn, David P. Woodruff, Samson Zhou

* To appear at STOC 2020 

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Average Case Column Subset Selection for Entrywise $\ell_1$-Norm Loss

Apr 16, 2020
Zhao Song, David P. Woodruff, Peilin Zhong

* NeurIPS 2019 

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LSF-Join: Locality Sensitive Filtering for Distributed All-Pairs Set Similarity Under Skew

Mar 06, 2020
Cyrus Rashtchian, Aneesh Sharma, David P. Woodruff

* WWW (The Web Conference) 2020 

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Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation

Jan 02, 2020
Ainesh Bakshi, Nadiia Chepurko, David P. Woodruff

* updating abstract 

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Sublinear Time Numerical Linear Algebra for Structured Matrices

Dec 12, 2019
Xiaofei Shi, David P. Woodruff


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Optimal Sketching for Kronecker Product Regression and Low Rank Approximation

Sep 29, 2019
Huaian Diao, Rajesh Jayaram, Zhao Song, Wen Sun, David P. Woodruff

* A preliminary version of this paper appeared in NeurIPS 2019 

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Total Least Squares Regression in Input Sparsity Time

Sep 27, 2019
Huaian Diao, Zhao Song, David P. Woodruff, Xin Yang


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The Communication Complexity of Optimization

Jun 13, 2019
Santosh S. Vempala, Ruosong Wang, David P. Woodruff


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Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel $k$-means Clustering

May 15, 2019
Manuel Fernandez, David P. Woodruff, Taisuke Yasuda

* 27 pages, to appear in ICML 2019 

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Dimensionality Reduction for Tukey Regression

May 14, 2019
Kenneth L. Clarkson, Ruosong Wang, David P. Woodruff

* To appear in ICML 2019 

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Low-Rank Approximation from Communication Complexity

Apr 22, 2019
Cameron Musco, Christopher Musco, David P. Woodruff


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Learning Two Layer Rectified Neural Networks in Polynomial Time

Nov 05, 2018
Ainesh Bakshi, Rajesh Jayaram, David P. Woodruff


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Towards a Zero-One Law for Entrywise Low Rank Approximation

Nov 04, 2018
Zhao Song, David P. Woodruff, Peilin Zhong


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Testing Matrix Rank, Optimally

Oct 18, 2018
Maria-Florina Balcan, Yi Li, David P. Woodruff, Hongyang Zhang

* 51 pages. To appear in SODA 2019 

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Approximation Algorithms for $\ell_0$-Low Rank Approximation

Oct 01, 2018
Karl Bringmann, Pavel Kolev, David P. Woodruff


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On Coresets for Logistic Regression

Sep 13, 2018
Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David P. Woodruff


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A PTAS for $\ell_p$-Low Rank Approximation

Jul 16, 2018
Frank Ban, Vijay Bhattiprolu, Karl Bringmann, Pavel Kolev, Euiwoong Lee, David P. Woodruff

* 71 pages 

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Matrix Completion and Related Problems via Strong Duality

Apr 25, 2018
Maria-Florina Balcan, Yingyu Liang, David P. Woodruff, Hongyang Zhang

* 37 pages, 4 figures 

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Relative Error Tensor Low Rank Approximation

Mar 29, 2018
Zhao Song, David P. Woodruff, Peilin Zhong


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