Cameron Musco
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
46
Venues
17
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 | SODA | Sublinear Time Low-Rank Approximation of Hankel Matrices. | Michael Kapralov, Cameron Musco, Kshiteej Sheth |
| 2025 | COLT | Sharper Bounds for Chebyshev Moment Matching, with Applications. | Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh |
| 2025 | ICML | Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems. | Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz, Bo Sun, Cameron Musco, Mohammad Hajiesmaili |
| 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 |
| 2024 | ICML | On the Role of Edge Dependency in Graph Generative Models. | Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis |
| 2024 | SODA | On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. | Raphael A. Meyer, Cameron Musco, Christopher Musco |
| 2024 | SODA | Sublinear Time Low-Rank Approximation of Toeplitz Matrices. | Cameron Musco, Kshiteej Sheth |
| 2023 | AISTATS | Optimal Sketching Bounds for Sparse Linear Regression. | Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff |
| 2023 | ICALP | Sublinear Time Eigenvalue Approximation via Random Sampling. | Rajarshi Bhattacharjee, Gregory Dexter, Petros Drineas, Cameron Musco, Archan Ray |
| 2023 | ICLR | Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs. | Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco |
| 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 | Toeplitz Low-Rank Approximation with Sublinear Query Complexity. | Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth |
| 2023 | SODA | Near-Linear Sample Complexity for | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2023 | WSDM | Local Edge Dynamics and Opinion Polarization. | Nikita Bhalla, Adam Lechowicz, Cameron Musco |
| 2022 | AAAI | Sublinear Time Approximation of Text Similarity Matrices. | Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco |
| 2022 | ESA | Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries. | Raghavendra Addanki, Andrew McGregor, Cameron Musco |
| 2022 | FOCS | Active Linear Regression for ℓp Norms and Beyond. | Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda |
| 2022 | ICLR | Fast Regression for Structured Inputs. | Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou |
| 2021 | AISTATS | Faster Kernel Interpolation for Gaussian Processes. | Mohit Yadav, Daniel Sheldon, Cameron Musco |
| 2021 | ALT | Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. | Raghavendra Addanki, Andrew McGregor, Cameron Musco |
| 2021 | ALT | Subspace Embeddings under Nonlinear Transformations. | Aarshvi Gajjar, Cameron Musco |
| 2021 | ICML | Faster Kernel Matrix Algebra via Density Estimation. | Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner |
| 2021 | ICML | DeepWalking Backwards: From Embeddings Back to Graphs. | Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis |
| 2020 | AISTATS | Importance Sampling via Local Sensitivity. | Anant Raj, Cameron Musco, Lester Mackey |
| 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 | ICML | Efficient Intervention Design for Causal Discovery with Latents. | Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco |
| 2020 | KDD | InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. | Sudhanshu Chanpuriya, Cameron 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 |
| 2019 | COLT | Learning to Prune: Speeding up Repeated Computations. | Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik |
| 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 | FOCS | Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices. | Cameron Musco, David P. Woodruff |
| 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 |
| 2016 | ICML | Faster Eigenvector Computation via Shift-and-Invert Preconditioning. | Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford |
| 2016 | PODC | Ant-Inspired Density Estimation via Random Walks: Extended Abstract. | Cameron Musco, Hsin-Hao Su, Nancy A. Lynch |
| 2015 | PODC | Distributed House-Hunting in Ant Colonies. | Mohsen Ghaffari, Cameron Musco, Tsvetomira Radeva, Nancy A. Lynch |
| 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 |