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Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices
11 April 2017
Cameron Musco
David P. Woodruff
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Papers citing
"Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices"
27 / 27 papers shown
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251
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Randomly Pivoted Partial Cholesky: Random How?
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Krylov Methods are (nearly) Optimal for Low-Rank Approximation
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354
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06 Apr 2023
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation
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Piotr Indyk
Praneeth Kacham
Sandeep Silwal
Samson Zhou
286
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0
01 Dec 2022
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
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13 Jul 2022
Improved analysis of randomized SVD for top-eigenvector approximation
International Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Ruo-Chun Tzeng
Po-An Wang
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Chi-Jen Lu
240
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16 Feb 2022
Low-Rank Approximation with
1
/
ε
1
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3
1/ε^{1/3}
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Matrix-Vector Products
Symposium on the Theory of Computing (STOC), 2022
Ainesh Bakshi
K. Clarkson
David P. Woodruff
468
21
0
10 Feb 2022
Sublinear Time Approximation of Text Similarity Matrices
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Nicholas Monath
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356
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17 Dec 2021
Learning a Latent Simplex in Input-Sparsity Time
International Conference on Learning Representations (ICLR), 2021
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Chiranjib Bhattacharyya
R. Kannan
David P. Woodruff
Samson Zhou
394
14
0
17 May 2021
Faster Kernel Matrix Algebra via Density Estimation
International Conference on Machine Learning (ICML), 2021
A. Backurs
Piotr Indyk
Cameron Musco
Tal Wagner
259
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0
16 Feb 2021
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
Nadiia Chepurko
K. Clarkson
L. Horesh
Honghao Lin
David P. Woodruff
838
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09 Nov 2020
Generalized Leverage Score Sampling for Neural Networks
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Ruoqi Shen
Zhao Song
Mengdi Wang
Zheng Yu
341
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21 Sep 2020
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions
Cameron Musco
Christopher Musco
126
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17 Apr 2020
Sublinear Time Numerical Linear Algebra for Structured Matrices
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Xiaofei Shi
David P. Woodruff
198
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12 Dec 2019
Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation
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Ainesh Bakshi
Nadiia Chepurko
David P. Woodruff
291
20
0
09 Dec 2019
Adversarially Robust Low Dimensional Representations
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Vaggos Chatziafratis
Xue Chen
Aravindan Vijayaraghavan
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413
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0
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Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
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Rajesh Jayaram
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David P. Woodruff
285
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29 Sep 2019
Sample-Optimal Low-Rank Approximation of Distance Matrices
Annual Conference Computational Learning Theory (COLT), 2019
Piotr Indyk
A. Vakilian
Tal Wagner
David P. Woodruff
172
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02 Jun 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel
k
k
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-means Clustering
International Conference on Machine Learning (ICML), 2019
Manuel Fernández
David P. Woodruff
T. Yasuda
211
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0
15 May 2019
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms
H. Avron
Michael Kapralov
Cameron Musco
Christopher Musco
A. Velingker
A. Zandieh
281
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0
20 Dec 2018
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Cameron Musco
David P. Woodruff
262
14
0
05 Nov 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
J. Tropp
A. Yurtsever
Madeleine Udell
Volkan Cevher
307
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0
18 Jun 2017
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