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Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices
v1v2v3 (latest)

Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices

11 April 2017
Cameron Musco
David P. Woodruff
ArXiv (abs)PDFHTML

Papers citing "Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices"

27 / 27 papers shown
Title
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
Ethan N. Epperly
J. Tropp
R. Webber
72
5
0
04 Oct 2024
Recent and Upcoming Developments in Randomized Numerical Linear Algebra
  for Machine Learning
Recent and Upcoming Developments in Randomized Numerical Linear Algebra for Machine Learning
Michał Dereziński
Michael W. Mahoney
85
11
0
17 Jun 2024
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning
Michal Dereziñski
Christopher Musco
Jiaming Yang
121
2
0
09 May 2024
Adaptive Retrieval and Scalable Indexing for k-NN Search with
  Cross-Encoders
Adaptive Retrieval and Scalable Indexing for k-NN Search with Cross-Encoders
Nishant Yadav
Nicholas Monath
Manzil Zaheer
Rob Fergus
Andrew McCallum
CMLRALM
69
1
0
06 May 2024
Randomly Pivoted Partial Cholesky: Random How?
Randomly Pivoted Partial Cholesky: Random How?
Stefan Steinerberger
51
1
0
17 Apr 2024
Hardness of Low Rank Approximation of Entrywise Transformed Matrix
  Products
Hardness of Low Rank Approximation of Entrywise Transformed Matrix Products
Tamás Sarlós
Xingyou Song
David P. Woodruff
Qiuyi
Qiuyi Zhang
80
4
0
03 Nov 2023
Relating tSNE and UMAP to Classical Dimensionality Reduction
Relating tSNE and UMAP to Classical Dimensionality Reduction
Andrew Draganov
Simon Dohn
FAtt
91
4
0
20 Jun 2023
Krylov Methods are (nearly) Optimal for Low-Rank Approximation
Krylov Methods are (nearly) Optimal for Low-Rank Approximation
Ainesh Bakshi
Shyam Narayanan
58
7
0
06 Apr 2023
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density
  Estimation
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation
Ainesh Bakshi
Piotr Indyk
Praneeth Kacham
Sandeep Silwal
Samson Zhou
104
4
0
01 Dec 2022
Randomly pivoted Cholesky: Practical approximation of a kernel matrix
  with few entry evaluations
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
Yifan Chen
Ethan N. Epperly
J. Tropp
R. Webber
121
33
0
13 Jul 2022
Improved analysis of randomized SVD for top-eigenvector approximation
Improved analysis of randomized SVD for top-eigenvector approximation
Ruo-Chun Tzeng
Po-An Wang
Florian Adriaens
Aristides Gionis
Chi-Jen Lu
38
1
0
16 Feb 2022
Low-Rank Approximation with $1/ε^{1/3}$ Matrix-Vector Products
Low-Rank Approximation with 1/ε1/31/ε^{1/3}1/ε1/3 Matrix-Vector Products
Ainesh Bakshi
K. Clarkson
David P. Woodruff
73
16
0
10 Feb 2022
Sublinear Time Approximation of Text Similarity Matrices
Sublinear Time Approximation of Text Similarity Matrices
Archan Ray
Nicholas Monath
Andrew McCallum
Cameron Musco
62
7
0
17 Dec 2021
Learning a Latent Simplex in Input-Sparsity Time
Learning a Latent Simplex in Input-Sparsity Time
Ainesh Bakshi
Chiranjib Bhattacharyya
R. Kannan
David P. Woodruff
Samson Zhou
140
10
0
17 May 2021
Faster Kernel Matrix Algebra via Density Estimation
Faster Kernel Matrix Algebra via Density Estimation
A. Backurs
Piotr Indyk
Cameron Musco
Tal Wagner
70
8
0
16 Feb 2021
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
Quantum-Inspired Algorithms from Randomized Numerical Linear Algebra
Nadiia Chepurko
K. Clarkson
L. Horesh
Honghao Lin
David P. Woodruff
60
24
0
09 Nov 2020
Generalized Leverage Score Sampling for Neural Networks
Generalized Leverage Score Sampling for Neural Networks
Jason D. Lee
Ruoqi Shen
Zhao Song
Mengdi Wang
Zheng Yu
71
43
0
21 Sep 2020
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions
Cameron Musco
Christopher Musco
45
12
0
17 Apr 2020
Sublinear Time Numerical Linear Algebra for Structured Matrices
Sublinear Time Numerical Linear Algebra for Structured Matrices
Xiaofei Shi
David P. Woodruff
54
17
0
12 Dec 2019
Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation
Robust and Sample Optimal Algorithms for PSD Low-Rank Approximation
Ainesh Bakshi
Nadiia Chepurko
David P. Woodruff
60
20
0
09 Dec 2019
Adversarially Robust Low Dimensional Representations
Adversarially Robust Low Dimensional Representations
Pranjal Awasthi
Vaggos Chatziafratis
Xue Chen
Aravindan Vijayaraghavan
AAMLOOD
103
12
0
29 Nov 2019
Optimal Sketching for Kronecker Product Regression and Low Rank
  Approximation
Optimal Sketching for Kronecker Product Regression and Low Rank Approximation
H. Diao
Rajesh Jayaram
Zhao Song
Wen Sun
David P. Woodruff
76
45
0
29 Sep 2019
Sample-Optimal Low-Rank Approximation of Distance Matrices
Sample-Optimal Low-Rank Approximation of Distance Matrices
Piotr Indyk
A. Vakilian
Tal Wagner
David P. Woodruff
53
36
0
02 Jun 2019
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel
  $k$-means Clustering
Tight Kernel Query Complexity of Kernel Ridge Regression and Kernel kkk-means Clustering
Manuel Fernández
David P. Woodruff
T. Yasuda
60
7
0
15 May 2019
A Universal Sampling Method for Reconstructing Signals with Simple
  Fourier Transforms
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms
H. Avron
Michael Kapralov
Cameron Musco
Christopher Musco
A. Velingker
A. Zandieh
64
49
0
20 Dec 2018
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?
Cameron Musco
David P. Woodruff
105
13
0
05 Nov 2017
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from
  Streaming Data
Fixed-Rank Approximation of a Positive-Semidefinite Matrix from Streaming Data
J. Tropp
A. Yurtsever
Madeleine Udell
Volkan Cevher
80
81
0
18 Jun 2017
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