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ORCIDChristopher Musco
- > Home > Persons > Christopher Musco
Publications
- 2025
[c56]Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh:
Sharper Bounds for Chebyshev Moment Matching, with Applications. COLT 2025: 4309-4358- [c52]Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson:
Near-optimal hierarchical matrix approximation from matrix-vector products. SODA 2025: 2656-2692 - [c51]Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray:
Improved Spectral Density Estimation via Explicit and Implicit Deflation. SODA 2025: 2693-2754 - [i66]Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel:
Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search. CoRR abs/2505.15636 (2025) - [i64]Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson:
Quasi-optimal hierarchically semi-separable matrix approximation. CoRR abs/2505.16937 (2025) - [i61]Noah Amsel, Pratyush Avi, Tyler Chen, Feyza Duman Keles, Chinmay Hegde, Cameron Musco, Christopher Musco, David Persson:
Query Efficient Structured Matrix Learning. CoRR abs/2507.19290 (2025) - 2024
- [c46]Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Nearly Optimal Approximation of Matrix Functions by the Lanczos Method. NeurIPS 2024 - [c45]Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel:
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. NeurIPS 2024 - [c43]Raphael A. Meyer, Cameron Musco, Christopher Musco:
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA 2024: 811-845 - [i60]Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco:
Fixed-sparsity matrix approximation from matrix-vector products. CoRR abs/2402.09379 (2024) - [i57]Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel:
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR abs/2405.18680 (2024) - [i55]Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson:
Near-optimal hierarchical matrix approximation from matrix-vector products. CoRR abs/2407.04686 (2024) - [i53]Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh:
Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond. CoRR abs/2408.12385 (2024) - [i50]Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray:
Improved Spectral Density Estimation via Explicit and Implicit Deflation. CoRR abs/2410.21690 (2024) - 2023
- [j4]Tyler Chen
, Anne Greenbaum, Cameron Musco, Christopher Musco:
Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation. SIAM J. Matrix Anal. Appl. 44(2): 670-692 (2023) - [c36]Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. PODS 2023: 169-181 - [c35]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. SODA 2023: 3959-4025 - [i49]Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang:
Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. CoRR abs/2301.05811 (2023) - [i48]Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method. CoRR abs/2303.03358 (2023) - [i47]Raphael A. Meyer, Cameron Musco, Christopher Musco:
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR abs/2305.02535 (2023) - 2022
- [j2]Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Error Bounds for Lanczos-Based Matrix Function Approximation. SIAM J. Matrix Anal. Appl. 43(2): 787-811 (2022) - [c33]Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda:
Active Linear Regression for ℓp Norms and Beyond. FOCS 2022: 744-753 - [c31]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Fast Regression for Structured Inputs. ICLR 2022 - [i38]Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Low-memory Krylov subspace methods for optimal rational matrix function approximation. CoRR abs/2202.11251 (2022) - [i37]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Fast Regression for Structured Inputs. CoRR abs/2203.07557 (2022) - [i34]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou:
Near-Linear Sample Complexity for Lp Polynomial Regression. CoRR abs/2211.06790 (2022) - 2021
- [c27]Cameron Musco, Christopher Musco, David P. Woodruff:
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation. ITCS 2021: 6:1-6:20 - [c23]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff:
Hutch++: Optimal Stochastic Trace Estimation. SOSA 2021: 142-155 - [i30]Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco:
Error bounds for Lanczos-based matrix function approximation. CoRR abs/2106.09806 (2021) - [i27]Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda:
Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. CoRR abs/2111.04888 (2021) - 2020
- [c22]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS 2020: 517-528 - [c21]Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco:
Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP 2020: 4796-4800 - [c20]Tamás Erdélyi, Cameron Musco, Christopher Musco:
Fourier Sparse Leverage Scores and Approximate Kernel Learning. NeurIPS 2020 - [c18]Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco:
Sample Efficient Toeplitz Covariance Estimation. SODA 2020: 378-397 - [c17]Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos:
Fast and Space Efficient Spectral Sparsification in Dynamic Streams. SODA 2020: 1814-1833 - [i26]Cameron Musco, Christopher Musco:
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions. CoRR abs/2004.08434 (2020) - [i25]Tamás Erdélyi, Cameron Musco, Christopher Musco:
Fourier Sparse Leverage Scores and Approximate Kernel Learning. CoRR abs/2006.07340 (2020) - [i22]Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff:
Hutch++: Optimal Stochastic Trace Estimation. CoRR abs/2010.09649 (2020) - 2019
- [c15]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
A universal sampling method for reconstructing signals with simple Fourier transforms. STOC 2019: 1051-1063 - [i21]Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri:
Faster Spectral Sparsification in Dynamic Streams. CoRR abs/1903.12165 (2019) - [i20]Cameron Musco, Christopher Musco, David P. Woodruff:
Low-Rank Approximation from Communication Complexity. CoRR abs/1904.09841 (2019) - [i19]Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco:
Sample Efficient Toeplitz Covariance Estimation. CoRR abs/1905.05643 (2019) - [i17]Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco:
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR abs/1911.08015 (2019) - 2018
- [c14]Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco:
Eigenvector Computation and Community Detection in Asynchronous Gossip Models. ICALP 2018: 159:1-159:14 - [c13]Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Babis Tsourakakis:
Inferring Networks From Random Walk-Based Node Similarities. NeurIPS 2018: 3708-3719 - [c12]Cameron Musco, Christopher Musco, Aaron Sidford:
Stability of the Lanczos Method for Matrix Function Approximation. SODA 2018: 1605-1624 - [c11]Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis:
Minimizing Polarization and Disagreement in Social Networks. WWW 2018: 369-378 - [i15]Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis:
Learning Networks from Random Walk-Based Node Similarities. CoRR abs/1801.07386 (2018) - [i14]Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco:
Eigenvector Computation and Community Detection in Asynchronous Gossip Models. CoRR abs/1804.08548 (2018) - [i13]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR abs/1804.09893 (2018) - [i12]Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou:
Near Optimal Linear Algebra in the Online and Sliding Window Models. CoRR abs/1805.03765 (2018) - [i11]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR abs/1812.08723 (2018) - 2017
- [j1]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. 46(1): 456-477 (2017) - [c9]Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh:
Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML 2017: 253-262 - [c8]Cameron Musco, Christopher Musco:
Recursive Sampling for the Nystrom Method. NIPS 2017: 3833-3845 - [c7]Michael B. Cohen, Cameron Musco, Christopher Musco:
Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling. SODA 2017: 1758-1777 - [i10]Cameron Musco, Christopher Musco, Aaron Sidford:
Stability of the Lanczos Method for Matrix Function Approximation. CoRR abs/1708.07788 (2017) - [i9]Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis:
Minimizing Polarization and Disagreement in Social Networks. CoRR abs/1712.09948 (2017) - 2016
- [c6]Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford:
Principal Component Projection Without Principal Component Analysis. ICML 2016: 2349-2357 - [i7]Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford:
Principal Component Projection Without Principal Component Analysis. CoRR abs/1602.06872 (2016) - [i6]Cameron Musco, Christopher Musco:
Provably Useful Kernel Matrix Approximation in Linear Time. CoRR abs/1605.07583 (2016) - 2015
- [c5]Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford:
Uniform Sampling for Matrix Approximation. ITCS 2015: 181-190 - [c3]Cameron Musco, Christopher Musco:
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition. NIPS 2015: 1396-1404 - [c2]Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu:
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. STOC 2015: 163-172 - [i5]Cameron Musco, Christopher Musco:
Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods. CoRR abs/1504.05477 (2015) - [i4]Michael B. Cohen, Cameron Musco, Christopher Musco:
Ridge Leverage Scores for Low-Rank Approximation. CoRR abs/1511.07263 (2015) - 2014
- [c1]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. FOCS 2014: 561-570 - [i3]Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford:
Single Pass Spectral Sparsification in Dynamic Streams. CoRR abs/1407.1289 (2014) - [i2]Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford:
Uniform Sampling for Matrix Approximation. CoRR abs/1408.5099 (2014) - [i1]Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu:
Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. CoRR abs/1410.6801 (2014)
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last updated on 2025-08-27 19:50 CEST by the dblp team
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