Cameron Musco

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All published works
Action Title Year Authors
+ PDF Chat Improved Spectral Density Estimation via Explicit and Implicit Deflation 2025 Rajarshi Bhattacharjee
Rajesh Jayaram
Cameron Musco
Christopher Musco
Archan Ray
+ PDF Chat Near-optimal hierarchical matrix approximation from matrix-vector products 2025 Tyler Chen
Feyza Duman Keles
Diana Halikias
Cameron Musco
Christopher Musco
David Persson
+ Local Edge Dynamics and Opinion Polarization 2024 Nikita Bhalla
Adam Lechowicz
Cameron Musco
+ PDF Chat Improved Spectral Density Estimation via Explicit and Implicit Deflation 2024 Rajarshi Bhattacharjee
Rajesh Jayaram
Cameron Musco
Christopher Musco
Archan Ray
+ PDF Chat Efficient and Private Marginal Reconstruction with Local Non-Negativity 2024 Brett Mullins
Miguel Fuentes
Yingtai Xiao
Daniel Kifer
Cameron Musco
Daniel Sheldon
+ PDF Chat Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond 2024 Cameron Musco
Christopher Musco
Lucas Rosenblatt
Apoorv Vikram Singh
+ PDF Chat Near-optimal hierarchical matrix approximation from matrix-vector products 2024 Tyler Chen
Feyza Duman Keles
Diana Halikias
Cameron Musco
Christopher Musco
David Persson
+ PDF Chat Competitive Algorithms for Online Knapsack with Succinct Predictions 2024 Mohammadreza Daneshvaramoli
Helia Karisani
Adam Lechowicz
Bo Sun
Cameron Musco
Mohammad Hajiesmaili
+ PDF Chat Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits 2024 Haya Diwan
Jinrui Gou
Cameron Musco
Christopher Musco
Torsten Suel
+ PDF Chat Sublinear Time Low-Rank Approximation of Toeplitz Matrices 2024 Cameron Musco
Kshiteej Sheth
+ PDF Chat Fixed-sparsity matrix approximation from matrix-vector products 2024 Noah Amsel
Tyler Chen
Feyza Duman Keles
Diana Halikias
Cameron Musco
Christopher Musco
+ Sublinear Time Eigenvalue Approximation via Random Sampling 2024 Rajarshi Bhattacharjee
Gregory Dexter
Petros Drineas
Cameron Musco
Archan Ray
+ PDF Chat On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation 2024 Raphael A. Meyer
Cameron Musco
Christopher Musco
+ PDF Chat Sublinear Time Low-Rank Approximation of Toeplitz Matrices 2024 Cameron Musco
Kshiteej Sheth
+ Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation 2023 Aline Bessa
Majid Daliri
Juliana Freire
Cameron Musco
Christopher Musco
Aécio Santos
Haoxiang Zhang
+ PDF Chat Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation 2023 Tyler Chen
Anne Greenbaum
Cameron Musco
Christopher Musco
+ Local Edge Dynamics and Opinion Polarization 2023 Nikita Bhalla
Adam Lechowicz
Cameron Musco
+ PDF Chat Near-Linear Sample Complexity for <i>L<sub>p</sub></i> Polynomial Regression 2023 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
Samson Zhou
+ PDF Chat Toeplitz Low-Rank Approximation with Sublinear Query Complexity 2023 Michael Kapralov
Hannah Lawrence
М. И. Макаров
Cameron Musco
Kshiteej Sheth
+ Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation 2023 Aline Bessa
Majid Daliri
Juliana Freire
Cameron Musco
Christopher Musco
Aécio Santos
Haoxiang Zhang
+ Near-Optimal Approximation of Matrix Functions by the Lanczos Method 2023 Noah Amsel
Tyler Chen
Anne Greenbaum
Cameron Musco
Chris Musco
+ No-regret Algorithms for Fair Resource Allocation 2023 Abhishek Sinha
Ativ Joshi
Rajarshi Bhattacharjee
Cameron Musco
Mohammad Hajiesmaili
+ Optimal Sketching Bounds for Sparse Linear Regression 2023 Tung Mai
Alexander Munteanu
Cameron Musco
Anup Rao
Chris Schwiegelshohn
David P. Woodruff
+ On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation 2023 Raphael A. Meyer
Cameron Musco
Christopher Musco
+ Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra 2023 Rajarshi Bhattacharjee
Gregory Dexter
Cameron Musco
Archan Ray
David P. Woodruff
+ Kernel Interpolation with Sparse Grids 2023 Mohit Yadav
Daniel Sheldon
Cameron Musco
+ Latent Random Steps as Relaxations of Max-Cut, Min-Cut, and More 2023 Sudhanshu Chanpuriya
Cameron Musco
+ On the Role of Edge Dependency in Graph Generative Models 2023 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Active Linear Regression for ℓ<sub>p</sub> Norms and Beyond 2022 Cameron Musco
Christopher Musco
David P. Woodruff
Taisuke Yasuda
+ PDF Chat Sublinear Time Approximation of Text Similarity Matrices 2022 Archan Ray
Nicholas Monath
Andrew McCallum
Cameron Musco
+ PDF Chat Error Bounds for Lanczos-Based Matrix Function Approximation 2022 Tyler Chen
Anne Greenbaum
Cameron Musco
Christopher Musco
+ Simplified Graph Convolution with Heterophily 2022 Sudhanshu Chanpuriya
Cameron Musco
+ Low-memory Krylov subspace methods for optimal rational matrix function approximation 2022 Tyler Chen
Anne Greenbaum
Cameron Musco
Christopher Musco
+ Fast Regression for Structured Inputs 2022 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
Samson Zhou
+ Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries 2022 Raghavendra Addanki
Andrew McGregor
Cameron Musco
+ PDF Chat A Basic Compositional Model for Spiking Neural Networks 2022 Nancy Lynch
Cameron Musco
+ Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs 2022 Sudhanshu Chanpuriya
Ryan A. Rossi
Sungchul Kim
Tong Yu
Jane Hoffswell
Nedim Lipka
Shunan Guo
Cameron Musco
+ Sample Constrained Treatment Effect Estimation 2022 Raghavendra Addanki
David Arbour
Tung Mai
Cameron Musco
Anup Rao
+ Near-Linear Sample Complexity for $L_p$ Polynomial Regression 2022 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
Samson Zhou
+ Toeplitz Low-Rank Approximation with Sublinear Query Complexity 2022 Michael Kapralov
Hannah Lawrence
М. И. Макаров
Cameron Musco
Kshiteej Sheth
+ On the Power of Edge Independent Graph Models 2021 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. 2021 Cameron Musco
Christopher Musco
David P. Woodruff
Taisuke Yasuda
+ An Interpretable Graph Generative Model with Heterophily. 2021 Sudhanshu Chanpuriya
Ryan A. Rossi
Anup Rao
Tung Mai
Nedim Lipka
Zhao Song
Cameron Musco
+ On the Power of Edge Independent Graph Models. 2021 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Faster Kernel Matrix Algebra via Density Estimation 2021 Artūrs Bačkurs
Piotr Indyk
Cameron Musco
Tal Wagner
+ PDF Chat Coresets for Classification -- Simplified and Strengthened 2021 Tung Mai
Anup Rao
Cameron Musco
+ Faster Kernel Interpolation for Gaussian Processes 2021 Mohit Yadav
Daniel Sheldon
Cameron Musco
+ Subspace Embeddings under Nonlinear Transformations 2021 Aarshvi Gajjar
Cameron Musco
+ Faster Kernel Matrix Algebra via Density Estimation 2021 Artūrs Bačkurs
Piotr Indyk
Cameron Musco
Tal Wagner
+ Faster Kernel Interpolation for Gaussian Processes 2021 Mohit Yadav
Daniel Sheldon
Cameron Musco
+ PDF Chat Hutch++: Optimal Stochastic Trace Estimation 2021 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
+ Coresets for Classification -- Simplified and Strengthened 2021 Tung Mai
Anup Rao
Cameron Musco
+ Sublinear Time Approximation of Text Similarity Matrices 2021 Archan Ray
Nicholas Monath
Andrew McCallum
Cameron Musco
+ Local Edge Dynamics and Opinion Polarization 2021 Nikita Bhalla
Adam Lechowicz
Cameron Musco
+ On the Power of Edge Independent Graph Models 2021 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Sublinear Time Eigenvalue Approximation via Random Sampling 2021 Rajarshi Bhattacharjee
Gregory Dexter
Petros Drineas
Cameron Musco
Archan Ray
+ DeepWalking Backwards: From Embeddings Back to Graphs 2021 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Faster Kernel Matrix Algebra via Density Estimation 2021 Artūrs Bačkurs
Piotr Indyk
Cameron Musco
Tal Wagner
+ Active Linear Regression for $\ell_p$ Norms and Beyond 2021 Cameron Musco
Christopher Musco
David P. Woodruff
Taisuke Yasuda
+ Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings 2021 Sudhanshu Chanpuriya
Ryan A. Rossi
Anup Rao
Tung Mai
Nedim Lipka
Zhao Song
Cameron Musco
+ Estimation of Shortest Path Covariance Matrices. 2020 Raj Kumar Maity
Cameron Musco
+ PDF Chat Near Optimal Linear Algebra in the Online and Sliding Window Models 2020 Vladimir Braverman
Petros Drineas
Cameron Musco
Christopher Musco
Jalaj Upadhyay
David P. Woodruff
Samson Zhou
+ Hutch++: Optimal Stochastic Trace Estimation 2020 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
+ Spiking Neural Networks Through the Lens of Streaming Algorithms 2020 Yael Hitron
Cameron Musco
Merav Parter
+ Fourier Sparse Leverage Scores and Approximate Kernel Learning 2020 Tamás Erdélyi
Cameron Musco
Christopher Musco
+ PDF Chat Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers 2020 Hannah Lawrence
Jerry Li
Cameron Musco
Christopher Musco
+ Projection-Cost-Preserving Sketches: Proof Strategies and Constructions 2020 Cameron Musco
Christopher Musco
+ Efficient Intervention Design for Causal Discovery with Latents 2020 Raghavendra Addanki
Shiva Prasad Kasiviswanathan
Andrew McGregor
Cameron Musco
+ InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity 2020 Sudhanshu Chanpuriya
Cameron Musco
+ Node Embeddings and Exact Low-Rank Representations of Complex Networks 2020 Sudhanshu Chanpuriya
Cameron Musco
Konstantinos Sotiropoulos
Charalampos E. Tsourakakis
+ Subspace Embeddings Under Nonlinear Transformations 2020 Aarshvi Gajjar
Cameron Musco
+ Model-specific Data Subsampling with Influence Functions 2020 Anant Raj
Cameron Musco
Lester Mackey
Nicoló Fusi
+ Intervention Efficient Algorithms for Approximate Learning of Causal Graphs 2020 Raghavendra Addanki
Andrew McGregor
Cameron Musco
+ Estimation of Shortest Path Covariance Matrices 2020 Raj Kumar Maity
Cameron Musco
+ Hutch++: Optimal Stochastic Trace Estimation 2020 Raphael A. Meyer
Cameron Musco
Christopher Musco
David P. Woodruff
+ Spiking Neural Networks Through the Lens of Streaming Algorithms 2020 Yael Hitron
Cameron Musco
Merav Parter
+ Fourier Sparse Leverage Scores and Approximate Kernel Learning 2020 Tamás Erdélyi
Cameron Musco
Christopher Musco
+ PDF Chat Sample Efficient Toeplitz Covariance Estimation 2019 Yonina C. Eldar
Jerry Li
Cameron Musco
Christopher Musco
+ Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers 2019 Hannah Lawrence
Jerry Li
Cameron Musco
Christopher Musco
+ PDF Chat A universal sampling method for reconstructing signals with simple Fourier transforms 2019 Haim Avron
Michael Kapralov
Cameron Musco
Christopher Musco
Ameya Velingker
Amir Zandieh
+ Sample Efficient Toeplitz Covariance Estimation 2019 Yonina C. Eldar
Jerry Li
Cameron Musco
Christopher Musco
+ Low-Rank Approximation from Communication Complexity 2019 Cameron Musco
Christopher Musco
David P. Woodruff
+ Faster Spectral Sparsification in Dynamic Streams. 2019 Michael Kapralov
Aida Mousavifar
Cameron Musco
Christopher Musco
Navid Nouri
+ Winner-Take-All Computation in Spiking Neural Networks 2019 Nancy Lynch
Cameron Musco
Merav Parter
+ Learning to Prune: Speeding up Repeated Computations 2019 Daniel Alabi
Adam Tauman Kalai
Katrina Ligett
Cameron Musco
Christos Tzamos
Ellen Vitercik
+ Toward a Characterization of Loss Functions for Distribution Learning 2019 Nika Haghtalab
Cameron Musco
Bo Waggoner
+ Importance Sampling via Local Sensitivity 2019 Anant Raj
Cameron Musco
Lester Mackey
+ Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation 2019 Cameron Musco
Christopher Musco
David P. Woodruff
+ Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers 2019 Hannah R. Lawrence
Jerry Li
Cameron Musco
Christopher Musco
+ Sample Efficient Toeplitz Covariance Estimation 2019 Yonina C. Eldar
Jerry Li
Cameron Musco
Christopher Musco
+ Faster Spectral Sparsification in Dynamic Streams 2019 Michael Kapralov
Aida Mousavifar
Cameron Musco
Christopher Musco
Navid Nouri
+ A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms 2018 Haim Avron
Michael Kapralov
Cameron Musco
Christopher Musco
Ameya Velingker
Amir Zandieh
+ A Basic Compositional Model for Spiking Neural Networks 2018 Nancy Lynch
Cameron Musco
+ Eigenvector Computation and Community Detection in Asynchronous Gossip Models 2018 Frederik Mallmann-Trenn
Cameron Musco
Christopher Musco
+ Eigenvector Computation and Community Detection in Asynchronous Gossip Models 2018 Frederik Mallmann-Trenn
Cameron Musco
Christopher Musco
+ Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees 2018 Haim Avron
Michael Kapralov
Cameron Musco
Christopher Musco
Ameya Velingker
Amir Zandieh
+ Learning Networks from Random Walk-Based Node Similarities 2018 Jeremy G. Hoskins
Cameron Musco
Christopher Musco
Charalampos E. Tsourakakis
+ PDF Chat Stability of the Lanczos Method for Matrix Function Approximation 2018 Cameron Musco
Christopher Musco
Aaron Sidford
+ Minimizing Polarization and Disagreement in Social Networks 2018 Cameron Musco
Christopher Musco
Charalampos E. Tsourakakis
+ Near Optimal Linear Algebra in the Online and Sliding Window Models 2018 Vladimir Braverman
Petros Drineas
Cameron Musco
Christopher Musco
Jalaj Upadhyay
David P. Woodruff
Samson Zhou
+ A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms 2018 Haim Avron
Michael Kapralov
Cameron Musco
Christopher Musco
Ameya Velingker
Amir Zandieh
+ Eigenvector Computation and Community Detection in Asynchronous Gossip Models 2018 Frederik Mallmann-Trenn
Cameron Musco
Christopher Musco
+ A Basic Compositional Model for Spiking Neural Networks 2018 Nancy Lynch
Cameron Musco
+ Minimizing Polarization and Disagreement in Social Networks 2017 Cameron Musco
Christopher Musco
Charalampos E. Tsourakakis
+ Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? 2017 Cameron Musco
David P. Woodruff
+ PDF Chat Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices 2017 Cameron Musco
David P. Woodruff
+ PDF Chat Ant-inspired density estimation via random walks 2017 Cameron Musco
Hsin-Hao Su
Nancy Lynch
+ Stability of the Lanczos Method for Matrix Function Approximation 2017 Cameron Musco
Christopher Musco
Aaron Sidford
+ Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks 2017 Nancy Lynch
Cameron Musco
Merav Parter
+ Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness 2017 Cameron Musco
Praneeth Netrapalli
Aaron Sidford
Shashanka Ubaru
David P. Woodruff
+ Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices 2017 Cameron Musco
David P. Woodruff
+ Input sparsity time low-rank approximation via ridge leverage score sampling 2017 Michael B. Cohen
Cameron Musco
Christopher Musco
+ Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling 2017 Michael B. Cohen
Cameron Musco
Christopher Musco
+ Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? 2017 Cameron Musco
David P. Woodruff
+ Recursive Sampling for the Nyström Method 2017 Cameron Musco
Christopher Musco
+ Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness 2017 Cameron Musco
Praneeth Netrapalli
Aaron Sidford
Shashanka Ubaru
David P. Woodruff
+ Minimizing Polarization and Disagreement in Social Networks 2017 Cameron Musco
Christopher Musco
Charalampos E. Tsourakakis
+ Stability of the Lanczos Method for Matrix Function Approximation 2017 Cameron Musco
Christopher Musco
Aaron Sidford
+ Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks 2017 Nancy Lynch
Cameron Musco
Merav Parter
+ Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices 2017 Cameron Musco
David P. Woodruff
+ Ant-Inspired Density Estimation via Random Walks 2016 Cameron Musco
Hsin-Hao Su
Nancy Lynch
+ Provably Useful Kernel Matrix Approximation in Linear Time. 2016 Cameron Musco
Christopher Musco
+ Online Row Sampling 2016 Michael B. Cohen
Cameron Musco
Jakub Pachocki
+ Ant-Inspired Density Estimation via Random Walks 2016 Cameron Musco
Hsin-Hao Su
Nancy Lynch
+ Principal Component Projection Without Principal Component Analysis 2016 Roy Frostig
Cameron Musco
Christopher Musco
Aaron Sidford
+ Faster Eigenvector Computation via Shift-and-Invert Preconditioning 2016 Dan Garber
Elad Hazan
Chi Jin
Sham M. Kakade
Cameron Musco
Praneeth Netrapalli
Aaron Sidford
+ Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks 2016 Nancy Lynch
Cameron Musco
Merav Parter
+ Recursive Sampling for the Nyström Method 2016 Cameron Musco
Christopher Musco
+ Principal Component Projection Without Principal Component Analysis 2016 Roy Frostig
Cameron Musco
Christopher Musco
Aaron Sidford
+ Online Row Sampling 2016 Michael B. Cohen
Cameron Musco
Jakub Pachocki
+ Ridge Leverage Scores for Low-Rank Approximation 2015 Michael B. Cohen
Cameron Musco
Christopher Musco
+ PDF Chat Distributed House-Hunting in Ant Colonies 2015 Mohsen Ghaffari
Cameron Musco
Tsvetomira Radeva
Nancy Lynch
+ PDF Chat Dimensionality Reduction for k-Means Clustering and Low Rank Approximation 2015 Michael B. Cohen
Sam Elder
Cameron Musco
Christopher Musco
Madalina Persu
+ Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition 2015 Cameron Musco
Christopher Musco
+ Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods. 2015 Cameron Musco
Christopher Musco
+ Stronger and Faster Approximate Singular Value Decomposition via the Block Lanczos Method 2015 Cameron Musco
Christopher Musco
+ PDF Chat Uniform Sampling for Matrix Approximation 2015 Michael B. Cohen
Yin Tat Lee
Cameron Musco
Christopher Musco
Richard Peng
Aaron Sidford
+ Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation 2015 Chi Jin
Sham M. Kakade
Cameron Musco
Praneeth Netrapalli
Aaron Sidford
+ Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition 2015 Cameron Musco
Christopher Musco
+ Distributed House-Hunting in Ant Colonies 2015 Mohsen Ghaffari
Cameron Musco
Tsvetomira Radeva
Nancy Lynch
+ Input Sparsity Time Low-Rank Approximation via Ridge Leverage Score Sampling 2015 Michael B. Cohen
Cameron Musco
Christopher Musco
+ Dimensionality Reduction for k-Means Clustering and Low Rank Approximation 2014 Michael B. Cohen
Sam Elder
Cameron Musco
Christopher Musco
Madalina Persu
+ PDF Chat Single Pass Spectral Sparsification in Dynamic Streams 2014 Michael Kapralov
Yin Tat Lee
Cameron Musco
Christopher Musco
Aaron Sidford
+ Uniform Sampling for Matrix Approximation 2014 Michael B. Cohen
Yin Tat Lee
Cameron Musco
Christopher Musco
Richard Peng
Aaron Sidford
+ Single Pass Spectral Sparsification in Dynamic Streams 2014 Michael Kapralov
Yin Tat Lee
Cameron Musco
Christopher Musco
Aaron Sidford
+ Single Pass Spectral Sparsification in Dynamic Streams 2014 Michael Kapralov
Yin Tat Lee
Cameron Musco
Christopher Musco
Aaron Sidford
+ Uniform Sampling for Matrix Approximation 2014 Michael B. Cohen
Yin Tat Lee
Cameron Musco
Christopher Musco
Richard Peng
Aaron Sidford
+ Dimensionality Reduction for k-Means Clustering and Low Rank Approximation 2014 Michael B. Cohen
Sam Elder
Cameron Musco
Christopher Musco
Madalina Persu
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Uniform Sampling for Matrix Approximation 2015 Michael B. Cohen
Yin Tat Lee
Cameron Musco
Christopher Musco
Richard Peng
Aaron Sidford
24
+ PDF Chat Low rank approximation and regression in input sparsity time 2013 Kenneth L. Clarkson
David P. Woodruff
20
+ Sketching as a Tool for Numerical Linear Algebra 2014 David P. Woodruff
18
+ PDF Chat OSNAP: Faster Numerical Linear Algebra Algorithms via Sparser Subspace Embeddings 2013 Jelani Nelson
Huy L. Nguyễn
18
+ PDF Chat Dimensionality Reduction for k-Means Clustering and Low Rank Approximation 2015 Michael B. Cohen
Sam Elder
Cameron Musco
Christopher Musco
Madalina Persu
16
+ PDF Chat Low-distortion subspace embeddings in input-sparsity time and applications to robust linear regression 2013 Xiangrui Meng
Michael W. Mahoney
12
+ PDF Chat Graph Sparsification by Effective Resistances 2011 Daniel A. Spielman
Nikhil Srivastava
11
+ Input sparsity time low-rank approximation via ridge leverage score sampling 2017 Michael B. Cohen
Cameron Musco
Christopher Musco
9
+ Fast randomized kernel ridge regression with statistical guarantees 2015 A. El Alaoui
Michael W. Mahoney
8
+ PDF Chat Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions 2011 Nathan Halko
Per‐Gunnar Martinsson
Joel A. Tropp
7
+ Fast Monte Carlo Algorithms for Matrices II: Computing a Low-Rank Approximation to a Matrix 2006 Petros Drineas
Ravi Kannan
Michael W. Mahoney
7
+ Sampling algorithms for l2 regression and applications 2006 Petros Drineas
Michael W. Mahoney
S. Muthukrishnan
7
+ An Introduction to Matrix Concentration Inequalities 2015 Joel A. Tropp
7
+ PDF Chat Fourier-Sparse Interpolation without a Frequency Gap 2016 Xue Chen
Daniel M. Kane
Eric Price
Zhao Song
7
+ PDF Chat Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems 2004 Daniel A. Spielman
Shang‐Hua Teng
7
+ PDF Chat Relative-Error $CUR$ Matrix Decompositions 2008 Petros Drineas
Michael W. Mahoney
S. Muthukrishnan
7
+ PDF Chat Twice-Ramanujan Sparsifiers 2012 Joshua Batson
Daniel A. Spielman
Nikhil Srivastava
7
+ Fast Monte Carlo Algorithms for Matrices III: Computing a Compressed Approximate Matrix Decomposition 2006 Petros Drineas
Ravi Kannan
Michael W. Mahoney
6
+ PDF Chat Near-Optimal Column-Based Matrix Reconstruction 2014 Christos Boutsidis
Petros Drineas
Malik Magdon‐Ismail
6
+ PDF Chat User-Friendly Tail Bounds for Sums of Random Matrices 2011 Joel A. Tropp
6
+ Recursive Sampling for the Nyström Method 2017 Cameron Musco
Christopher Musco
6
+ Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition 2015 Cameron Musco
Christopher Musco
6
+ PDF Chat Randomized Algorithms for Matrices and Data 2012 Michael W. Mahoney
6
+ PDF Chat A universal sampling method for reconstructing signals with simple Fourier transforms 2019 Haim Avron
Michael Kapralov
Cameron Musco
Christopher Musco
Ameya Velingker
Amir Zandieh
6
+ Scikit-learn: Machine Learning in Python 2012 Fabián Pedregosa
Gaël Varoquaux
Alexandre Gramfort
Vincent Michel
Bertrand Thirion
Olivier Grisel
Mathieu Blondel
Peter Prettenhofer
Ron J. Weiss
Vincent Dubourg
5
+ A unified framework for approximating and clustering data 2011 Dan Feldman
Michael Langberg
5
+ PDF Chat Nearly Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems 2014 Daniel A. Spielman
Shang‐Hua Teng
5
+ PDF Chat On the Stability and Accuracy of Least Squares Approximations 2013 Albert Cohen
Mark A. Davenport
D. Leviatan
5
+ PDF Chat Sample Efficient Toeplitz Covariance Estimation 2019 Yonina C. Eldar
Jerry Li
Cameron Musco
Christopher Musco
5
+ On the Nyström Method for Approximating a Gram Matrix for Improved Kernel-Based Learning 2005 Petros Drineas
Michael W. Mahoney
5
+ PDF Chat Analog-to-Digital Cognitive Radio: Sampling, Detection, and Hardware 2018 Déborah Cohen
Shahar Tsiper
Yonina C. Eldar
5
+ PDF Chat Blind Multiband Signal Reconstruction: Compressed Sensing for Analog Signals 2009 Moshe Mishali
Yonina C. Eldar
5
+ PDF Chat Exact and Stable Covariance Estimation From Quadratic Sampling via Convex Programming 2015 Yuxin Chen
Yuejie Chi
Andrea Goldsmith
5
+ Fast monte-carlo algorithms for finding low-rank approximations 2004 Alan Frieze
Ravi Kannan
Santosh Vempala
4
+ Optimal CUR Matrix Decompositions 2014 Christos Boutsidis
David P. Woodruff
4
+ High-Dimensional Statistics: A Non-Asymptotic Viewpoint 2019 Martin J. Wainwright
4
+ A nearly-mlogn time solver for SDD linear systems 2011 Ioannis Koutis
Gary L. Miller
Richard Peng
4
+ Fast Estimation of $tr(f(A))$ via Stochastic Lanczos Quadrature 2017 Shashanka Ubaru
Jie Chen
Yousef Saad
4
+ PDF Chat Numerical methods for the QCDd overlap operator. I. Sign-function and error bounds 2002 Jasper van den Eshof
Andreas Frommer
Thomas Lippert
Klaus Schilling
H.A. van der Vorst
4
+ PDF Chat Sparse Doppler Sensing Based on Nested Arrays 2018 Regev Cohen
Yonina C. Eldar
4
+ Randomized algorithms for matrices and data 2011 Michael W. Mahoney
4
+ On Coresets for Logistic Regression 2018 Alexander Munteanu
Chris Schwiegelshohn
Christian Sohler
David P. Woodruff
4
+ PDF Chat SYMMETRIC GAUGE FUNCTIONS AND UNITARILY INVARIANT NORMS 1960 L. Mirsky
4
+ Revisiting the Nystrom Method for Improved Large-Scale Machine Learning 2013 Alex Gittens
Michael W. Mahoney
4
+ Fast Monte Carlo Algorithms for Matrices I: Approximating Matrix Multiplication 2006 Petros Drineas
Ravi Kannan
Michael W. Mahoney
4
+ Principal Component Projection Without Principal Component Analysis 2016 Roy Frostig
Cameron Musco
Christopher Musco
Aaron Sidford
4
+ PDF Chat Simple and deterministic matrix sketching 2013 Edo Liberty
4
+ Spectral partitioning of random graphs 2001 Frank McSherry
4
+ PDF Chat Low-rank matrix completion using alternating minimization 2013 Prateek Jain
Praneeth Netrapalli
Sujay Sanghavi
4
+ PDF Chat Coherence motivated sampling and convergence analysis of least squares polynomial Chaos regression 2015 Jerrad Hampton
Alireza Doostan
4