Christopher Musco
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
46
Venues
19
Active years
2014–2026
Best venue rank
A*
Where they publish
Papers
46 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | COLT | Query Efficient Structured Matrix Learning. | Noah Amsel, Pratyush Avi, Tyler Chen, Feyza Duman Keles, Chinmay Hegde, Christopher Musco, Cameron Musco, David Persson |
| 2026 | ESA | Nearly Instance Optimal Sparse Matrix Approximation from Matrix-Vector Products. | Christopher Musco, Indu Ramesh |
| 2026 | SODA | Efficiently Constructing Sparse Navigable Graphs. | Alex Conway, Laxman Dhulipala, Martin Farach-Colton, Rob Johnson, Ben Landrum, Christopher Musco, Yarin Shechter, Torsten Suel, Richard Wen |
| 2026 | SODA | Does block size matter in randomized block Krylov low-rank approximation? | Tyler Chen, Ethan N. Epperly, Raphael A. Meyer, Christopher Musco, Akash Rao |
| 2025 | COLT | Sharper Bounds for Chebyshev Moment Matching, with Applications. | Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh |
| 2025 | ICLR | Matrix Product Sketching via Coordinated Sampling. | Majid Daliri, Juliana Freire, Danrong Li, Christopher Musco |
| 2025 | ICLR | Provably Accurate Shapley Value Estimation via Leverage Score Sampling. | Christopher Musco, R. Teal Witter |
| 2025 | ISIT | Coupling Without Communication and Drafter-Invariant Speculative Decoding. | Majid Daliri, Christopher Musco, Ananda Theertha Suresh |
| 2025 | SODA | Improved Spectral Density Estimation via Explicit and Implicit Deflation. | Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray |
| 2025 | SODA | Near-optimal hierarchical matrix approximation from matrix-vector products. | Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson |
| 2025 | SODA | Faster Linear Systems and Matrix Norm Approximation via Multi-level Sketched Preconditioning. | Michal Derezinski, Christopher Musco, Jiaming Yang |
| 2024 | AAAI | A Simple and Practical Method for Reducing the Disparate Impact of Differential Privacy. | Lucas Rosenblatt, Julia Stoyanovich, Christopher Musco |
| 2024 | COLT | Agnostic Active Learning of Single Index Models with Linear Sample Complexity. | Aarshvi Gajjar, Wai Ming Tai, Xingyu Xu, Chinmay Hegde, Christopher Musco, Yi Li |
| 2024 | COLT | Faster Spectral Density Estimation and Sparsification in the Nuclear Norm (Extended Abstract). | Yujia Jin, Ishani Karmarkar, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh |
| 2024 | ICLR | Improved Active Learning via Dependent Leverage Score Sampling. | Atsushi Shimizu, Xiaoou Cheng, Christopher Musco, Jonathan Weare |
| 2024 | SODA | On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. | Raphael A. Meyer, Cameron Musco, Christopher Musco |
| 2023 | AISTATS | Active Learning for Single Neuron Models with Lipschitz Non-Linearities. | Aarshvi Gajjar, Christopher Musco, Chinmay Hegde |
| 2023 | COLT | Moments, Random Walks, and Limits for Spectrum Approximation. | Yujia Jin, Christopher Musco, Aaron Sidford, Apoorv Vikram Singh |
| 2023 | ESA | Efficient Block Approximate Matrix Multiplication. | Chuhan Yang, Christopher Musco |
| 2023 | ICML | Dimensionality Reduction for General KDE Mode Finding. | Xinyu Luo, Christopher Musco, Cas Widdershoven |
| 2023 | PODS | Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. | Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Acio S. R. Santos, Haoxiang Zhang |
| 2023 | SODA | Near-Linear Sample Complexity for | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2022 | FOCS | Active Linear Regression for ℓp Norms and Beyond. | Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda |
| 2022 | ICDE | A Sketch-based Index for Correlated Dataset Search. | Acio S. R. Santos, Aline Bessa, Christopher Musco, Juliana Freire |
| 2022 | ICLR | Fast Regression for Structured Inputs. | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2022 | STOC | Sublinear time spectral density estimation. | Vladimir Braverman, Aditya Krishnan, Christopher Musco |
| 2021 | AAAI | Graph Learning for Inverse Landscape Genetics. | Prathamesh Dharangutte, Christopher Musco |
| 2021 | ESA | Finding an Approximate Mode of a Kernel Density Estimate. | Jasper C. H. Lee, Jerry Li, Christopher Musco, Jeff M. Phillips, Wai Ming Tai |
| 2021 | SIGMOD | Correlation Sketches for Approximate Join-Correlation Queries. | Acio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco, Juliana Freire |
| 2021 | SIGMOD | Public Transport Planning: When Transit Network Connectivity Meets Commuting Demand. | Sheng Wang, Yuan Sun, Christopher Musco, Zhifeng Bao |
| 2020 | FOCS | Near Optimal Linear Algebra in the Online and Sliding Window Models. | Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou |
| 2020 | ICASSP | Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. | Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco |
| 2020 | SODA | Sample Efficient Toeplitz Covariance Estimation. | Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco |
| 2020 | SODA | Fast and Space Efficient Spectral Sparsification in Dynamic Streams. | Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos |
| 2020 | WSDM | Analyzing the Impact of Filter Bubbles on Social Network Polarization. | Uthsav Chitra, Christopher Musco |
| 2019 | STOC | A universal sampling method for reconstructing signals with simple Fourier transforms. | Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh |
| 2018 | ICALP | Eigenvector Computation and Community Detection in Asynchronous Gossip Models. | Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco |
| 2018 | WWW | Minimizing Polarization and Disagreement in Social Networks. | Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis |
| 2018 | SODA | Stability of the Lanczos Method for Matrix Function Approximation. | Cameron Musco, Christopher Musco, Aaron Sidford |
| 2017 | ALENEX | Determining Tournament Payout Structures for Daily Fantasy Sports. | Christopher Musco, Maxim Sviridenko, Justin Thaler |
| 2017 | ICML | Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. | Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh |
| 2017 | SODA | Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling. | Michael B. Cohen, Cameron Musco, Christopher Musco |
| 2016 | ICML | Principal Component Projection Without Principal Component Analysis. | Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford |
| 2015 | NDSS | Principled Sampling for Anomaly Detection. | Brendan Juba, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, Martin C. Rinard |
| 2015 | STOC | Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. | Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu |
| 2014 | FOCS | Single Pass Spectral Sparsification in Dynamic Streams. | Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford |