Christopher Musco

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 97

Top Venues

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
Faster Spectral Density Estimation and Sparsification in the Nuclear Norm. CoRR (2024)
Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare
Improved Active Learning via Dependent Leverage Score Sampling. ICLR (2024)
Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
Fixed-sparsity matrix approximation from matrix-vector products. CoRR (2024)
Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. AAAI (2024)
Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
Near-optimal hierarchical matrix approximation from matrix-vector products. CoRR (2024)
Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
Sampling Methods for Inner Product Sketching. Proc. VLDB Endow. 17 (9) (2024)
Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract). COLT (2024)
Raphael A. Meyer, Cameron Musco, Christopher Musco
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA (2024)
Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
Simple Analysis of Priority Sampling. SOSA (2024)
Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR (2024)
Michal Derezinski, Christopher Musco, Jiaming Yang
Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning. CoRR (2024)
Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li
Agnostic Active Learning of Single Index Models with Linear Sample Complexity. CoRR (2024)
Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li
Agnostic Active Learning of Single Index Models with Linear Sample Complexity. COLT (2024)
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)
Aarshvi Gajjar, Christopher Musco, Chinmay Hegde
Active Learning for Single Neuron Models with Lipschitz Non-Linearities. AISTATS (2023)
Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco
A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. CoRR (2023)
Prathamesh Dharangutte, Christopher Musco
A Tight Analysis of Hutchinson's Diagonal Estimator. SOSA (2023)
Xinyu Luo, Christopher Musco, Cas Widdershoven
Dimensionality Reduction for General KDE Mode Finding. ICML (2023)
Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
Simple Analysis of Priority Sampling. CoRR (2023)
Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
Moments, Random Walks, and Limits for Spectrum Approximation. CoRR (2023)
Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare
Improved Active Learning via Dependent Leverage Score Sampling. CoRR (2023)
Chuhan Yang, Christopher Musco
Efficient Block Approximate Matrix Multiplication. ESA (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. CoRR (2023)
Arun Jambulapati, Jerry Li, Christopher Musco, Kirankumar Shiragur, Aaron Sidford, Kevin Tian
Structured Semidefinite Programming for Recovering Structured Preconditioners. NeurIPS (2023)
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) (2023)
Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh
Moments, Random Walks, and Limits for Spectrum Approximation. COLT (2023)
Majid Daliri, Juliana Freire, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
Sampling Methods for Inner Product Sketching. CoRR (2023)
Raphael A. Meyer, Cameron Musco, Christopher Musco
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR (2023)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. SODA (2023)
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 (2023)
Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method. CoRR (2023)
David Persson, Raphael A. Meyer, Christopher Musco
Algorithm-agnostic low-rank approximation of operator monotone matrix functions. CoRR (2023)
Xinyu Luo, Christopher Musco, Cas Widdershoven
Dimensionality Reduction for General KDE Mode Finding. CoRR (2023)
Aarshvi Gajjar, Chinmay Hegde, Christopher Musco
Active Learning for Single Neuron Models with Lipschitz Non-Linearities. CoRR (2022)
Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Low-memory Krylov subspace methods for optimal rational matrix function approximation. CoRR (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Fast Regression for Structured Inputs. ICLR (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Fast Regression for Structured Inputs. CoRR (2022)
Vladimir Braverman, Aditya Krishnan, Christopher Musco
Sublinear time spectral density estimation. STOC (2022)
Aécio S. R. Santos, Aline Bessa, Christopher Musco, Juliana Freire
A Sketch-based Index for Correlated Dataset Search. ICDE (2022)
Mengxi Wu, Yi-jen Chiang, Christopher Musco
Streaming Approach to In Situ Selection of Key Time Steps for Time-Varying Volume Data. Comput. Graph. Forum 41 (3) (2022)
Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
Active Linear Regression for ℓp Norms and Beyond. FOCS (2022)
Prathamesh Dharangutte, Christopher Musco
A Tight Analysis of Hutchinson's Diagonal Estimator. CoRR (2022)
Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Error Bounds for Lanczos-Based Matrix Function Approximation. SIAM J. Matrix Anal. Appl. 43 (2) (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. CoRR (2022)
Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. CoRR (2021)
Christopher Musco, Indu Ramesh, Johan Ugander, R. Teal Witter
How to Quantify Polarization in Models of Opinion Dynamics. CoRR (2021)
Prathamesh Dharangutte, Christopher Musco
Dynamic Trace Estimation. CoRR (2021)
Prathamesh Dharangutte, Christopher Musco
Graph Learning for Inverse Landscape Genetics. AAAI (2021)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
Hutch++: Optimal Stochastic Trace Estimation. SOSA (2021)
Prathamesh Dharangutte, Christopher Musco
Dynamic Trace Estimation. NeurIPS (2021)
Aécio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco, Juliana Freire
Correlation Sketches for Approximate Join-Correlation Queries. CoRR (2021)
Vladimir Braverman, Aditya Krishnan, Christopher Musco
Linear and Sublinear Time Spectral Density Estimation. CoRR (2021)
Aécio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco, Juliana Freire
Correlation Sketches for Approximate Join-Correlation Queries. SIGMOD Conference (2021)
Cameron Musco, Christopher Musco, David P. Woodruff
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation. ITCS (2021)
Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
Finding an Approximate Mode of a Kernel Density Estimate. ESA (2021)
Sheng Wang, Yuan Sun, Christopher Musco, Zhifeng Bao
Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. SIGMOD Conference (2021)
Sheng Wang, Yuan Sun, Christopher Musco, Zhifeng Bao
Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. CoRR (2021)
Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Error bounds for Lanczos-based matrix function approximation. CoRR (2021)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
Hutch++: Optimal Stochastic Trace Estimation. CoRR (2020)
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)
Tamás Erdélyi, Cameron Musco, Christopher Musco
Fourier Sparse Leverage Scores and Approximate Kernel Learning. CoRR (2020)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. SODA (2020)
Cameron Musco, Christopher Musco
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions. CoRR (2020)
Uthsav Chitra, Christopher Musco
Analyzing the Impact of Filter Bubbles on Social Network Polarization. WSDM (2020)
Tamás Erdélyi, Cameron Musco, Christopher Musco
Fourier Sparse Leverage Scores and Approximate Kernel Learning. NeurIPS (2020)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP (2020)
Raphael A. Meyer, Christopher Musco
The Statistical Cost of Robust Kernel Hyperparameter Tuning. CoRR (2020)
Prathamesh Dharangutte, Christopher Musco
Graph Learning for Inverse Landscape Genetics. CoRR (2020)
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)
Raphael A. Meyer, Christopher Musco
The Statistical Cost of Robust Kernel Hyperparameter Turning. NeurIPS (2020)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR (2019)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. CoRR (2019)
Uthsav Chitra, Christopher Musco
Understanding Filter Bubbles and Polarization in Social Networks. CoRR (2019)
Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai
Finding the Mode of a Kernel Density Estimate. CoRR (2019)
Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri
Faster Spectral Sparsification in Dynamic Streams. CoRR (2019)
Cameron Musco, Christopher Musco, David P. Woodruff
Low-Rank Approximation from Communication Complexity. CoRR (2019)
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)
Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
Minimizing Polarization and Disagreement in Social Networks. WWW (2018)
Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
Eigenvector Computation and Community Detection in Asynchronous Gossip Models. ICALP (2018)
Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
Eigenvector Computation and Community Detection in Asynchronous Gossip Models. CoRR (2018)
Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Babis Tsourakakis
Inferring Networks From Random Walk-Based Node Similarities. NeurIPS (2018)
Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
Learning Networks from Random Walk-Based Node Similarities. CoRR (2018)
Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR (2018)
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 (2018)
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 (2018)
Cameron Musco, Christopher Musco, Aaron Sidford
Stability of the Lanczos Method for Matrix Function Approximation. SODA (2018)
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)
Cameron Musco, Christopher Musco
Recursive Sampling for the Nystrom Method. NIPS (2017)
Christopher Musco, Maxim Sviridenko, Justin Thaler
Determining Tournament Payout Structures for Daily Fantasy Sports. ALENEX (2017)
Cameron Musco, Christopher Musco, Aaron Sidford
Stability of the Lanczos Method for Matrix Function Approximation. CoRR (2017)
Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
Minimizing Polarization and Disagreement in Social Networks. CoRR (2017)
Michael B. Cohen, Cameron Musco, Christopher Musco
Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling. SODA (2017)
Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. 46 (1) (2017)
Cameron Musco, Christopher Musco
Provably Useful Kernel Matrix Approximation in Linear Time. CoRR (2016)
Christopher Musco, Maxim Sviridenko, Justin Thaler
Determining Tournament Payout Structures for Daily Fantasy Sports. CoRR (2016)
Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
Principal Component Projection Without Principal Component Analysis. ICML (2016)
Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
Principal Component Projection Without Principal Component Analysis. CoRR (2016)
Cameron Musco, Christopher Musco
Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods. CoRR (2015)
Cameron Musco, Christopher Musco
Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition. NIPS (2015)
Michael B. Cohen, Cameron Musco, Christopher Musco
Ridge Leverage Scores for Low-Rank Approximation. CoRR (2015)

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Publication Activity (10 Years)

Top Topics

Top Venues

Christopher Musco