Cameron Musco

ORCID

Publication Activity (10 Years)

Years Active: 2014-2024
Publications (10 Years): 137

Top Venues

Massachusetts Institute of Technology, Cambridge, USA (PHD)

Education History

Massachusetts Institute of Technology, Cambridge, USA

PHD

Publications

Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
Fixed-sparsity matrix approximation from matrix-vector products. CoRR (2024)
Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. ITCS (2024)
Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz, Bo Sun, Cameron Musco, Mohammad Hajiesmaili
Competitive Algorithms for Online Knapsack with Succinct Predictions. CoRR (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)
Raphael A. Meyer, Cameron Musco, Christopher Musco
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA (2024)
Cameron Musco, Kshiteej Sheth
Sublinear Time Low-Rank Approximation of Toeplitz Matrices. SODA (2024)
Rajarshi Bhattacharjee, Gregory Dexter, Petros Drineas, Cameron Musco, Archan Ray
Sublinear Time Eigenvalue Approximation via Random Sampling. Algorithmica 86 (6) (2024)
Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR (2024)
Cameron Musco, Kshiteej Sheth
Sublinear Time Low-Rank Approximation of Toeplitz Matrices. CoRR (2024)
Rajarshi Bhattacharjee, Gregory Dexter, Petros Drineas, Cameron Musco, Archan Ray
Sublinear Time Eigenvalue Approximation via Random Sampling. ICALP (2023)
Tung Mai, Alexander Munteanu, Cameron Musco, Anup B. Rao, Chris Schwiegelshohn, David P. Woodruff
Optimal Sketching Bounds for Sparse Linear Regression. CoRR (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. PODS (2023)
Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff
Optimal Sketching Bounds for Sparse Linear Regression. AISTATS (2023)
Mohit Yadav, Daniel Sheldon, Cameron Musco
Kernel Interpolation with Sparse Grids. CoRR (2023)
Nikita Bhalla, Adam Lechowicz, Cameron Musco
Local Edge Dynamics and Opinion Polarization. WSDM (2023)
Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. SODA (2023)
Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, David P. Woodruff
Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. CoRR (2023)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
On the Role of Edge Dependency in Graph Generative Models. CoRR (2023)
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs. ICLR (2023)
Sudhanshu Chanpuriya, Cameron Musco
Latent Random Steps as Relaxations of Max-Cut, Min-Cut, and More. CoRR (2023)
Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili
No-regret Algorithms for Fair Resource Allocation. 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)
Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili
No-regret Algorithms for Fair Resource Allocation. CoRR (2023)
Raphael A. Meyer, Cameron Musco, Christopher Musco
On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR (2023)
Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao
Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. NeurIPS (2023)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. SODA (2023)
Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco
Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. NeurIPS (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)
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries. CoRR (2022)
Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Low-memory Krylov subspace methods for optimal rational matrix function approximation. CoRR (2022)
Mohit Yadav, Daniel R. Sheldon, Cameron Musco
Kernel Interpolation with Sparse Grids. NeurIPS (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)
Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
Sublinear Time Approximation of Text Similarity Matrices. AAAI (2022)
Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
Active Linear Regression for ℓp Norms and Beyond. FOCS (2022)
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
Sample Constrained Treatment Effect Estimation. CoRR (2022)
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs. CoRR (2022)
Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
Sample Constrained Treatment Effect Estimation. NeurIPS (2022)
Nancy A. Lynch, Cameron Musco
A Basic Compositional Model for Spiking Neural Networks. A Journey from Process Algebra via Timed Automata to Model Learning (2022)
Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
Toeplitz Low-Rank Approximation with Sublinear Query Complexity. CoRR (2022)
Sudhanshu Chanpuriya, Cameron Musco
Simplified Graph Convolution with Heterophily. NeurIPS (2022)
Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum
Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS (2022)
Sudhanshu Chanpuriya, Cameron Musco
Simplified Graph Convolution with Heterophily. 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)
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries. ESA (2022)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
Polynomial Regression. CoRR (2022)
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Faster Kernel Matrix Algebra via Density Estimation. ICML (2021)
Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. CoRR (2021)
Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
Faster Kernel Matrix Algebra via Density Estimation. CoRR (2021)
Aarshvi Gajjar, Cameron Musco
Subspace Embeddings under Nonlinear Transformations. ALT (2021)
Mohit Yadav, Daniel Sheldon, Cameron Musco
Faster Kernel Interpolation for Gaussian Processes. CoRR (2021)
Rajarshi Bhattacharjee, Cameron Musco, Archan Ray
Sublinear Time Eigenvalue Approximation via Random Sampling. CoRR (2021)
Tung Mai, Cameron Musco, Anup Rao
Coresets for Classification - Simplified and Strengthened. NeurIPS (2021)
Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
Hutch++: Optimal Stochastic Trace Estimation. SOSA (2021)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
DeepWalking Backwards: From Embeddings Back to Graphs. ICML (2021)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
On the Power of Edge Independent Graph Models. NeurIPS (2021)
Cameron Musco, Christopher Musco, David P. Woodruff
Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation. ITCS (2021)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
On the Power of Edge Independent Graph Models. CoRR (2021)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
DeepWalking Backwards: From Embeddings Back to Graphs. CoRR (2021)
Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
Sublinear Time Approximation of Text Similarity Matrices. CoRR (2021)
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. ALT (2021)
Mohit Yadav, Daniel Sheldon, Cameron Musco
Faster Kernel Interpolation for Gaussian Processes. AISTATS (2021)
Tung Mai, Anup B. Rao, Cameron Musco
Coresets for Classification - Simplified and Strengthened. CoRR (2021)
Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco
An Interpretable Graph Generative Model with Heterophily. CoRR (2021)
Nikita Bhalla, Adam Lechowicz, Cameron Musco
Local Edge Dynamics and Opinion Polarization. CoRR (2021)
Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
Error bounds for Lanczos-based matrix function approximation. CoRR (2021)
Sudhanshu Chanpuriya, Cameron Musco
InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. KDD (2020)
Raj Kumar Maity, Cameron Musco
Estimation of Shortest Path Covariance Matrices. CoRR (2020)
Aarshvi Gajjar, Cameron Musco
Subspace Embeddings Under Nonlinear Transformations. CoRR (2020)
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)
Yael Hitron, Nancy A. Lynch, Cameron Musco, Merav Parter
Random Sketching, Clustering, and Short-Term Memory in Spiking Neural Networks. ITCS (2020)
Yael Hitron, Cameron Musco, Merav Parter
Spiking Neural Networks Through the Lens of Streaming Algorithms. DISC (2020)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. SODA (2020)
Yael Hitron, Cameron Musco, Merav Parter
Spiking Neural Networks Through the Lens of Streaming Algorithms. CoRR (2020)
Cameron Musco, Christopher Musco
Projection-Cost-Preserving Sketches: Proof Strategies and Constructions. CoRR (2020)
Anant Raj, Cameron Musco, Lester Mackey
Importance Sampling via Local Sensitivity. AISTATS (2020)
Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco
Efficient Intervention Design for Causal Discovery with Latents. CoRR (2020)
Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco
Efficient Intervention Design for Causal Discovery with Latents. ICML (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)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
Node Embeddings and Exact Low-Rank Representations of Complex Networks. NeurIPS (2020)
Michael B. Cohen, Cameron Musco, Jakub Pachocki
Online Row Sampling. Theory Comput. 16 (2020)
Raghavendra Addanki, Andrew McGregor, Cameron Musco
Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. 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)
Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi
Model-specific Data Subsampling with Influence Functions. CoRR (2020)
Sudhanshu Chanpuriya, Cameron Musco
InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. CoRR (2020)
Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
Node Embeddings and Exact Low-Rank Representations of Complex Networks. CoRR (2020)
Nancy A. Lynch, Cameron Musco, Merav Parter
Winner-Take-All Computation in Spiking Neural Networks. CoRR (2019)
Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR (2019)
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
Learning to Prune: Speeding up Repeated Computations. CoRR (2019)
Anant Raj, Cameron Musco, Lester Mackey
Importance Sampling via Local Sensitivity. CoRR (2019)
Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
Sample Efficient Toeplitz Covariance Estimation. CoRR (2019)
Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri
Faster Spectral Sparsification in Dynamic Streams. CoRR (2019)
Nika Haghtalab, Cameron Musco, Bo Waggoner
Toward a Characterization of Loss Functions for Distribution Learning. CoRR (2019)
Cameron Musco, Christopher Musco, David P. Woodruff
Low-Rank Approximation from Communication Complexity. CoRR (2019)
Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
Learning to Prune: Speeding up Repeated Computations. COLT (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)

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Publication Activity (10 Years)

Top Topics

Top Venues

Cameron Musco