Christopher Musco

139 papers A* 43A 7B 1Misc 1Journal 78Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	An Exact Algorithm for the Unanimous Vote Problem. SOSA Feyza Duman Keles, Lisa Hellerstein, Kunal Marwaha, Christopher Musco, Xinchen Yang
2026	A*	`conf`	Does block size matter in randomized block Krylov low-rank approximation? SODA Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao
2026	A*	`conf`	Efficiently Constructing Sparse Navigable Graphs. SODA Alex Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, Richard Wen
2026	J	`jnl`	Fixed-Sparsity Matrix Approximation from Matrix-Vector Products. SIAM J. Matrix Anal. Appl. Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
2026	J	`jnl`	PolySHAP: Extending KernelSHAP with Interaction-Informed Polynomial Regression. CoRR Fabian Fumagalli, R. Teal Witter, Christopher Musco
2025	J	`jnl`	Algorithm-Agnostic Low-Rank Approximation of Operator Monotone Matrix Functions. SIAM J. Matrix Anal. Appl. David Persson, Raphael A. Meyer, Christopher Musco
2025	J	`jnl`	An Exact Algorithm for the Unanimous Vote Problem. CoRR Feyza Duman Keles, Lisa Hellerstein, Kunal Marwaha, Christopher Musco, Xinchen Yang
2025	B	`conf`	Coupling Without Communication and Drafter-Invariant Speculative Decoding. ISIT Majid Daliri, Christopher Musco, Ananda Theertha Suresh
2025	J	`jnl`	Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search. CoRR Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2025	J	`jnl`	Does block size matter in randomized block Krylov low-rank approximation? CoRR Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao
2025	J	`jnl`	Efficiently Constructing Sparse Navigable Graphs. CoRR Alexander Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, Richard Wen
2025	A*	`conf`	Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning. SODA Michal Derezinski, Christopher Musco, Jiaming Yang
2025	A*	`conf`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. SODA Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
2025	A*	`conf`	Matrix Product Sketching via Coordinated Sampling. ICLR Majid Daliri, Juliana Freire, Danrong Li, Christopher Musco
2025	J	`jnl`	Matrix Product Sketching via Coordinated Sampling. CoRR Majid Daliri, Juliana Freire, Danrong Li, Christopher Musco
2025	A*	`conf`	Near-optimal hierarchical matrix approximation from matrix-vector products. SODA Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2025	A*	`conf`	Provably Accurate Shapley Value Estimation via Leverage Score Sampling. ICLR Christopher Musco, R. Teal Witter
2025	J	`jnl`	Quasi-optimal hierarchically semi-separable matrix approximation. CoRR Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2025	J	`jnl`	Query Efficient Structured Matrix Learning. CoRR Noah Amsel, Pratyush Avi, Tyler Chen, Feyza Duman Keles, Chinmay Hegde, Cameron Musco, Christopher Musco, David Persson
2025	J	`jnl`	Randomized block-Krylov subspace methods for low-rank approximation of matrix functions. CoRR David Persson, Tyler Chen, Christopher Musco
2025	J	`jnl`	Regression-adjusted Monte Carlo Estimators for Shapley Values and Probabilistic Values. CoRR R. Teal Witter, Yurong Liu, Christopher Musco
2025	A*	`conf`	Sharper Bounds for Chebyshev Moment Matching, with Applications. COLT Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh
2025	J	`jnl`	The Polar Express: Optimal Matrix Sign Methods and Their Application to the Muon Algorithm. CoRR Noah Amsel, David Persson, Christopher Musco, Robert Gower
2024	A*	`conf`	A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. AAAI Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
2024	A*	`conf`	Agnostic Active Learning of Single Index Models with Linear Sample Complexity. COLT Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li
2024	J	`jnl`	Agnostic Active Learning of Single Index Models with Linear Sample Complexity. CoRR Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li
2024	A*	`conf`	Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm. NeurIPS R. Teal Witter, Christopher Musco
2024	J	`jnl`	Benchmarking Estimators for Natural Experiments: A Novel Dataset and a Doubly Robust Algorithm. CoRR R. Teal Witter, Christopher Musco
2024	J	`jnl`	Coupling without Communication and Drafter-Invariant Speculative Decoding. CoRR Majid Daliri, Christopher Musco, Ananda Theertha Suresh
2024	J	`jnl`	Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning. CoRR Michal Derezinski, Christopher Musco, Jiaming Yang
2024	A*	`conf`	Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract). COLT Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
2024	J	`jnl`	Faster Spectral Density Estimation and Sparsification in the Nuclear Norm. CoRR Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
2024	J	`jnl`	Fixed-sparsity matrix approximation from matrix-vector products. CoRR Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
2024	A*	`conf`	Improved Active Learning via Dependent Leverage Score Sampling. ICLR Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare
2024	J	`jnl`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. CoRR Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
2024	A*	`conf`	Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. NeurIPS Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2024	J	`jnl`	Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2024	J	`jnl`	Near-optimal hierarchical matrix approximation from matrix-vector products. CoRR Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2024	A*	`conf`	Nearly Optimal Approximation of Matrix Functions by the Lanczos Method. NeurIPS Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2024	A*	`conf`	On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA Raphael A. Meyer, Cameron Musco, Christopher Musco
2024	J	`jnl`	Provably Accurate Shapley Value Estimation via Leverage Score Sampling. CoRR Christopher Musco, R. Teal Witter
2024	J	`jnl`	Sampling Methods for Inner Product Sketching. Proc. VLDB Endow. Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2024	J	`jnl`	Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond. CoRR Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh
2024	—	`conf`	Simple Analysis of Priority Sampling. SOSA Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2023	J	`jnl`	A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. CoRR Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
2023	—	`conf`	A Tight Analysis of Hutchinson's Diagonal Estimator. SOSA Prathamesh Dharangutte, Christopher Musco
2023	A	`conf`	Active Learning for Single Neuron Models with Lipschitz Non-Linearities. AISTATS Aarshvi Gajjar, Christopher Musco, Chinmay Hegde
2023	J	`jnl`	Algorithm-agnostic low-rank approximation of operator monotone matrix functions. CoRR David Persson, Raphael A. Meyer, Christopher Musco
2023	A*	`conf`	Dimensionality Reduction for General KDE Mode Finding. ICML Xinyu Luo, Christopher Musco, Cas Widdershoven
2023	J	`jnl`	Dimensionality Reduction for General KDE Mode Finding. CoRR Xinyu Luo, Christopher Musco, Cas Widdershoven
2023	A	`conf`	Efficient Block Approximate Matrix Multiplication. ESA Chuhan Yang, Christopher Musco
2023	J	`jnl`	Improved Active Learning via Dependent Leverage Score Sampling. CoRR Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare
2023	J	`jnl`	Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation. SIAM J. Matrix Anal. Appl. Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2023	A*	`conf`	Moments, Random Walks, and Limits for Spectrum Approximation. COLT Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
2023	J	`jnl`	Moments, Random Walks, and Limits for Spectrum Approximation. CoRR Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
2023	A*	`conf`	Near-Linear Sample Complexity for SODA Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2023	J	`jnl`	Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method. CoRR Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2023	J	`jnl`	On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco
2023	J	`jnl`	Sampling Methods for Inner Product Sketching. CoRR Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2023	J	`jnl`	Simple Analysis of Priority Sampling. CoRR Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2023	A*	`conf`	Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	J	`jnl`	Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
2023	A*	`conf`	Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. PODS Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2023	J	`jnl`	Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. CoRR Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2022	A*	`conf`	A Sketch-based Index for Correlated Dataset Search. ICDE Aécio S. R. Santos, Aline Bessa, Christopher Musco, Juliana Freire
2022	J	`jnl`	A Tight Analysis of Hutchinson's Diagonal Estimator. CoRR Prathamesh Dharangutte, Christopher Musco
2022	J	`jnl`	Active Learning for Single Neuron Models with Lipschitz Non-Linearities. CoRR Aarshvi Gajjar, Chinmay Hegde, Christopher Musco
2022	A*	`conf`	Active Linear Regression for ℓp Norms and Beyond. FOCS Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
2022	J	`jnl`	Error Bounds for Lanczos-Based Matrix Function Approximation. SIAM J. Matrix Anal. Appl. Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2022	A*	`conf`	Fast Regression for Structured Inputs. ICLR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Fast Regression for Structured Inputs. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Low-memory Krylov subspace methods for optimal rational matrix function approximation. CoRR Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2022	J	`jnl`	Near-Linear Sample Complexity for L CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Streaming Approach to In Situ Selection of Key Time Steps for Time-Varying Volume Data. Comput. Graph. Forum Mengxi Wu, Yi-Jen Chiang, Christopher Musco
2022	A*	`conf`	Sublinear time spectral density estimation. STOC Vladimir Braverman, Aditya Krishnan, Christopher Musco
2021	J	`jnl`	Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. CoRR Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
2021	—	`conf`	Correlation Sketches for Approximate Join-Correlation Queries. SIGMOD Conference Aécio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco, Juliana Freire
2021	J	`jnl`	Correlation Sketches for Approximate Join-Correlation Queries. CoRR Aécio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco, Juliana Freire
2021	A*	`conf`	Dynamic Trace Estimation. NeurIPS Prathamesh Dharangutte, Christopher Musco
2021	J	`jnl`	Dynamic Trace Estimation. CoRR Prathamesh Dharangutte, Christopher Musco
2021	J	`jnl`	Error bounds for Lanczos-based matrix function approximation. CoRR Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2021	A	`conf`	Finding an Approximate Mode of a Kernel Density Estimate. ESA Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
2021	A*	`conf`	Graph Learning for Inverse Landscape Genetics. AAAI Prathamesh Dharangutte, Christopher Musco
2021	J	`jnl`	How to Quantify Polarization in Models of Opinion Dynamics. CoRR Christopher Musco, Indu Ramesh, Johan Ugander, R. Teal Witter
2021	—	`conf`	Hutch++: Optimal Stochastic Trace Estimation. SOSA Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
2021	J	`jnl`	Linear and Sublinear Time Spectral Density Estimation. CoRR Vladimir Braverman, Aditya Krishnan, Christopher Musco
2021	—	`conf`	Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. SIGMOD Conference Sheng Wang, Yuan Sun, Christopher Musco, Zhifeng Bao
2021	J	`jnl`	Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. CoRR Sheng Wang, Yuan Sun, Christopher Musco, Zhifeng Bao
2021	A	`conf`	Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation. ITCS Cameron Musco, Christopher Musco, David P. Woodruff
2020	A	`conf`	Analyzing the Impact of Filter Bubbles on Social Network Polarization. WSDM Uthsav Chitra, Christopher Musco
2020	A*	`conf`	Fast and Space Efficient Spectral Sparsification in Dynamic Streams. SODA Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos
2020	A*	`conf`	Fourier Sparse Leverage Scores and Approximate Kernel Learning. NeurIPS Tamás Erdélyi, Cameron Musco, Christopher Musco
2020	J	`jnl`	Fourier Sparse Leverage Scores and Approximate Kernel Learning. CoRR Tamás Erdélyi, Cameron Musco, Christopher Musco
2020	J	`jnl`	Graph Learning for Inverse Landscape Genetics. CoRR Prathamesh Dharangutte, Christopher Musco
2020	J	`jnl`	Hutch++: Optimal Stochastic Trace Estimation. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
2020	Misc	`conf`	Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
2020	A*	`conf`	Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2020	J	`jnl`	Projection-Cost-Preserving Sketches: Proof Strategies and Constructions. CoRR Cameron Musco, Christopher Musco
2020	A*	`conf`	Sample Efficient Toeplitz Covariance Estimation. SODA Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
2020	J	`jnl`	The Statistical Cost of Robust Kernel Hyperparameter Tuning. CoRR Raphael A. Meyer, Christopher Musco
2020	A*	`conf`	The Statistical Cost of Robust Kernel Hyperparameter Turning. NeurIPS Raphael A. Meyer, Christopher Musco
2019	A*	`conf`	A universal sampling method for reconstructing signals with simple Fourier transforms. STOC Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2019	J	`jnl`	Faster Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri
2019	J	`jnl`	Finding the Mode of a Kernel Density Estimate. CoRR Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
2019	J	`jnl`	Low-Rank Approximation from Communication Complexity. CoRR Cameron Musco, Christopher Musco, David P. Woodruff
2019	J	`jnl`	Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
2019	J	`jnl`	Sample Efficient Toeplitz Covariance Estimation. CoRR Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
2019	J	`jnl`	Understanding Filter Bubbles and Polarization in Social Networks. CoRR Uthsav Chitra, Christopher Musco
2018	J	`jnl`	A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A*	`conf`	Eigenvector Computation and Community Detection in Asynchronous Gossip Models. ICALP Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
2018	J	`jnl`	Eigenvector Computation and Community Detection in Asynchronous Gossip Models. CoRR Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
2018	—	`—`	Faster linear algebra for data analysis and machine learning. Christopher Musco
2018	A*	`conf`	Inferring Networks From Random Walk-Based Node Similarities. NeurIPS Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Babis Tsourakakis
2018	J	`jnl`	Learning Networks from Random Walk-Based Node Similarities. CoRR Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2018	A*	`conf`	Minimizing Polarization and Disagreement in Social Networks. WWW Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2018	J	`jnl`	Near Optimal Linear Algebra in the Online and Sliding Window Models CoRR Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2018	J	`jnl`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A*	`conf`	Stability of the Lanczos Method for Matrix Function Approximation. SODA Cameron Musco, Christopher Musco, Aaron Sidford
2017	A	`conf`	Determining Tournament Payout Structures for Daily Fantasy Sports. ALENEX Christopher Musco, Maxim Sviridenko, Justin Thaler
2017	A*	`conf`	Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling. SODA Michael B. Cohen, Cameron Musco, Christopher Musco
2017	J	`jnl`	Minimizing Polarization and Disagreement in Social Networks. CoRR Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2017	A*	`conf`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2017	—	`conf`	Recursive Sampling for the Nystrom Method. NIPS Cameron Musco, Christopher Musco
2017	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2017	J	`jnl`	Stability of the Lanczos Method for Matrix Function Approximation. CoRR Cameron Musco, Christopher Musco, Aaron Sidford
2016	J	`jnl`	Determining Tournament Payout Structures for Daily Fantasy Sports. CoRR Christopher Musco, Maxim Sviridenko, Justin Thaler
2016	A*	`conf`	Principal Component Projection Without Principal Component Analysis. ICML Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
2016	J	`jnl`	Principal Component Projection Without Principal Component Analysis. CoRR Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
2016	J	`jnl`	Provably Useful Kernel Matrix Approximation in Linear Time. CoRR Cameron Musco, Christopher Musco
2015	A*	`conf`	Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. STOC Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu
2015	A*	`conf`	Principled Sampling for Anomaly Detection. NDSS Brendan Juba, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, Martin C. Rinard
2015	—	`conf`	Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition. NIPS Cameron Musco, Christopher Musco
2015	J	`jnl`	Ridge Leverage Scores for Low-Rank Approximation. CoRR Michael B. Cohen, Cameron Musco, Christopher Musco
2015	J	`jnl`	Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods. CoRR Cameron Musco, Christopher Musco
2015	A	`conf`	Uniform Sampling for Matrix Approximation. ITCS Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford
2014	J	`jnl`	Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. CoRR Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu
2014	A*	`conf`	Single Pass Spectral Sparsification in Dynamic Streams. FOCS Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	J	`jnl`	Uniform Sampling for Matrix Approximation. CoRR Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford