Cameron Musco - RankMe

175 papers A* 54A 15B 2Misc 1Journal 96Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A	`conf`	Fairness in the k-Server Problem. ITCS Mohammadreza Daneshvaramoli, Mohammad Hajiesmaili, Shahin Kamali, Helia Karisani, Cameron Musco
2026	J	`jnl`	Fast Private Adaptive Query Answering for Large Data Domains. CoRR Miguel Fuentes, Brett Mullins, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
2026	J	`jnl`	Fixed-Sparsity Matrix Approximation from Matrix-Vector Products. SIAM J. Matrix Anal. Appl. Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
2026	A*	`conf`	Sublinear Time Low-Rank Approximation of Hankel Matrices. SODA Michael Kapralov, Cameron Musco, Kshiteej Sheth
2026	A	`conf`	The Secretary Problem with Predictions and a Chosen Order. ITCS Helia Karisani, Mohammadreza Daneshvaramoli, Hedyeh Beyhaghi, Mohammad Hajiesmaili, Cameron Musco
2026	J	`jnl`	The Secretary Problem with Predictions and a Chosen Order. CoRR Helia Karisani, Mohammadreza Daneshvaramoli, Hedyeh Beyhaghi, Mohammad Hajiesmaili, Cameron Musco
2025	J	`jnl`	A Note on Fine-Grained Quantum Reductions for Linear Algebraic Problems. CoRR Kyle Doney, Cameron Musco
2025	J	`jnl`	Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search. CoRR Yousef Al-Jazzazi, Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2025	J	`jnl`	Fairness in the k-Server Problem. CoRR Mohammadreza Daneshvaramoli, Helia Karisani, Mohammad Hajiesmaili, Shahin Kamali, Cameron Musco
2025	A*	`conf`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. SODA Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
2025	J	`jnl`	Local Edge Dynamics and Opinion Polarization. ACM Trans. Intell. Syst. Technol. Nikita Bhalla, Adam Lechowicz, Cameron Musco
2025	A*	`conf`	Near-Optimal Consistency-Robustness Trade-Offs for Learning-Augmented Online Knapsack Problems. ICML Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz, Bo Sun, Cameron Musco, Mohammad Hajiesmaili
2025	A*	`conf`	Near-optimal hierarchical matrix approximation from matrix-vector products. SODA Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2025	J	`jnl`	Quasi-optimal hierarchically semi-separable matrix approximation. CoRR Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2025	J	`jnl`	Query Efficient Structured Matrix Learning. CoRR Noah Amsel, Pratyush Avi, Tyler Chen, Feyza Duman Keles, Chinmay Hegde, Cameron Musco, Christopher Musco, David Persson
2025	A*	`conf`	Sharper Bounds for Chebyshev Moment Matching, with Applications. COLT Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh
2025	J	`jnl`	Sublinear Time Low-Rank Approximation of Hankel Matrices. CoRR Michael Kapralov, Cameron Musco, Kshiteej Sheth
2024	J	`jnl`	Competitive Algorithms for Online Knapsack with Succinct Predictions. CoRR Mohammadreza Daneshvaramoli, Helia Karisani, Adam Lechowicz, Bo Sun, Cameron Musco, Mohammad Hajiesmaili
2024	A*	`conf`	Efficient and Private Marginal Reconstruction with Local Non-Negativity. NeurIPS Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel R. Sheldon
2024	J	`jnl`	Efficient and Private Marginal Reconstruction with Local Non-Negativity. CoRR Brett Mullins, Miguel Fuentes, Yingtai Xiao, Daniel Kifer, Cameron Musco, Daniel Sheldon
2024	J	`jnl`	Fixed-sparsity matrix approximation from matrix-vector products. CoRR Noah Amsel, Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco
2024	A*	`conf`	Gaussian Process Bandits for Top-k Recommendations. NeurIPS Mohit Yadav, Cameron Musco, Daniel R. Sheldon
2024	J	`jnl`	Improved Spectral Density Estimation via Explicit and Implicit Deflation. CoRR Rajarshi Bhattacharjee, Rajesh Jayaram, Cameron Musco, Christopher Musco, Archan Ray
2024	A*	`conf`	Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. NeurIPS Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2024	J	`jnl`	Navigable Graphs for High-Dimensional Nearest Neighbor Search: Constructions and Limits. CoRR Haya Diwan, Jinrui Gou, Cameron Musco, Christopher Musco, Torsten Suel
2024	J	`jnl`	Near-optimal hierarchical matrix approximation from matrix-vector products. CoRR Tyler Chen, Feyza Duman Keles, Diana Halikias, Cameron Musco, Christopher Musco, David Persson
2024	A*	`conf`	Nearly Optimal Approximation of Matrix Functions by the Lanczos Method. NeurIPS Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2024	A*	`conf`	On the Role of Edge Dependency in Graph Generative Models. ICML Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2024	A*	`conf`	On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. SODA Raphael A. Meyer, Cameron Musco, Christopher Musco
2024	J	`jnl`	Sharper Bounds for Chebyshev Moment Matching with Applications to Differential Privacy and Beyond. CoRR Cameron Musco, Christopher Musco, Lucas Rosenblatt, Apoorv Vikram Singh
2024	J	`jnl`	Sublinear Time Eigenvalue Approximation via Random Sampling. Algorithmica Rajarshi Bhattacharjee, Gregory Dexter, Petros Drineas, Cameron Musco, Archan Ray
2024	A*	`conf`	Sublinear Time Low-Rank Approximation of Toeplitz Matrices. SODA Cameron Musco, Kshiteej Sheth
2024	J	`jnl`	Sublinear Time Low-Rank Approximation of Toeplitz Matrices. CoRR Cameron Musco, Kshiteej Sheth
2024	A	`conf`	Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. ITCS Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff
2023	A*	`conf`	Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs. ICLR Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco
2023	A*	`conf`	Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings. NeurIPS Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco
2023	A*	`conf`	Finite Population Regression Adjustment and Non-asymptotic Guarantees for Treatment Effect Estimation. NeurIPS Mehrdad Ghadiri, David Arbour, Tung Mai, Cameron Musco, Anup B. Rao
2023	J	`jnl`	Kernel Interpolation with Sparse Grids. CoRR Mohit Yadav, Daniel Sheldon, Cameron Musco
2023	J	`jnl`	Latent Random Steps as Relaxations of Max-Cut, Min-Cut, and More. CoRR Sudhanshu Chanpuriya, Cameron Musco
2023	A	`conf`	Local Edge Dynamics and Opinion Polarization. WSDM Nikita Bhalla, Adam Lechowicz, Cameron Musco
2023	J	`jnl`	Low-Memory Krylov Subspace Methods for Optimal Rational Matrix Function Approximation. SIAM J. Matrix Anal. Appl. Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2023	A*	`conf`	Near-Linear Sample Complexity for SODA Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2023	J	`jnl`	Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method. CoRR Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2023	A*	`conf`	No-regret Algorithms for Fair Resource Allocation. NeurIPS Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad Hajiesmaili
2023	J	`jnl`	No-regret Algorithms for Fair Resource Allocation. CoRR Abhishek Sinha, Ativ Joshi, Rajarshi Bhattacharjee, Cameron Musco, Mohammad H. Hajiesmaili
2023	J	`jnl`	On the Role of Edge Dependency in Graph Generative Models. CoRR Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2023	J	`jnl`	On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco
2023	A	`conf`	Optimal Sketching Bounds for Sparse Linear Regression. AISTATS Tung Mai, Alexander Munteanu, Cameron Musco, Anup Rao, Chris Schwiegelshohn, David P. Woodruff
2023	J	`jnl`	Optimal Sketching Bounds for Sparse Linear Regression. CoRR Tung Mai, Alexander Munteanu, Cameron Musco, Anup B. Rao, Chris Schwiegelshohn, David P. Woodruff
2023	A*	`conf`	Sublinear Time Eigenvalue Approximation via Random Sampling. ICALP Rajarshi Bhattacharjee, Gregory Dexter, Petros Drineas, Cameron Musco, Archan Ray
2023	A*	`conf`	Toeplitz Low-Rank Approximation with Sublinear Query Complexity. SODA Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
2023	J	`jnl`	Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra. CoRR Rajarshi Bhattacharjee, Gregory Dexter, Cameron Musco, Archan Ray, Sushant Sachdeva, David P. Woodruff
2023	A*	`conf`	Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. PODS Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2023	J	`jnl`	Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation. CoRR Aline Bessa, Majid Daliri, Juliana Freire, Cameron Musco, Christopher Musco, Aécio S. R. Santos, Haoxiang Zhang
2022	—	`conf`	A Basic Compositional Model for Spiking Neural Networks. A Journey from Process Algebra via Timed Automata to Model Learning Nancy A. Lynch, Cameron Musco
2022	A*	`conf`	Active Linear Regression for ℓp Norms and Beyond. FOCS Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
2022	J	`jnl`	Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs. CoRR Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim, Tong Yu, Jane Hoffswell, Nedim Lipka, Shunan Guo, Cameron Musco
2022	J	`jnl`	Error Bounds for Lanczos-Based Matrix Function Approximation. SIAM J. Matrix Anal. Appl. Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2022	A*	`conf`	Fast Regression for Structured Inputs. ICLR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	J	`jnl`	Fast Regression for Structured Inputs. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	A*	`conf`	Kernel Interpolation with Sparse Grids. NeurIPS Mohit Yadav, Daniel R. Sheldon, Cameron Musco
2022	J	`jnl`	Low-memory Krylov subspace methods for optimal rational matrix function approximation. CoRR Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2022	A*	`conf`	Modeling Transitivity and Cyclicity in Directed Graphs via Binary Code Box Embeddings. NeurIPS Dongxu Zhang, Michael Boratko, Cameron Musco, Andrew McCallum
2022	J	`jnl`	Near-Linear Sample Complexity for L CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff, Samson Zhou
2022	A	`conf`	Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries. ESA Raghavendra Addanki, Andrew McGregor, Cameron Musco
2022	J	`jnl`	Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries. CoRR Raghavendra Addanki, Andrew McGregor, Cameron Musco
2022	A*	`conf`	Sample Constrained Treatment Effect Estimation. NeurIPS Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
2022	J	`jnl`	Sample Constrained Treatment Effect Estimation. CoRR Raghavendra Addanki, David Arbour, Tung Mai, Cameron Musco, Anup Rao
2022	A*	`conf`	Simplified Graph Convolution with Heterophily. NeurIPS Sudhanshu Chanpuriya, Cameron Musco
2022	J	`jnl`	Simplified Graph Convolution with Heterophily. CoRR Sudhanshu Chanpuriya, Cameron Musco
2022	A*	`conf`	Sublinear Time Approximation of Text Similarity Matrices. AAAI Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
2022	J	`jnl`	Toeplitz Low-Rank Approximation with Sublinear Query Complexity. CoRR Michael Kapralov, Hannah Lawrence, Mikhail Makarov, Cameron Musco, Kshiteej Sheth
2021	J	`jnl`	Active Sampling for Linear Regression Beyond the $\ell_2$ Norm. CoRR Cameron Musco, Christopher Musco, David P. Woodruff, Taisuke Yasuda
2021	J	`jnl`	An Interpretable Graph Generative Model with Heterophily. CoRR Sudhanshu Chanpuriya, Ryan A. Rossi, Anup B. Rao, Tung Mai, Nedim Lipka, Zhao Song, Cameron Musco
2021	A*	`conf`	Coresets for Classification - Simplified and Strengthened. NeurIPS Tung Mai, Cameron Musco, Anup Rao
2021	J	`jnl`	Coresets for Classification - Simplified and Strengthened. CoRR Tung Mai, Anup B. Rao, Cameron Musco
2021	A*	`conf`	DeepWalking Backwards: From Embeddings Back to Graphs. ICML Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2021	J	`jnl`	DeepWalking Backwards: From Embeddings Back to Graphs. CoRR Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2021	J	`jnl`	Error bounds for Lanczos-based matrix function approximation. CoRR Tyler Chen, Anne Greenbaum, Cameron Musco, Christopher Musco
2021	A	`conf`	Faster Kernel Interpolation for Gaussian Processes. AISTATS Mohit Yadav, Daniel Sheldon, Cameron Musco
2021	J	`jnl`	Faster Kernel Interpolation for Gaussian Processes. CoRR Mohit Yadav, Daniel Sheldon, Cameron Musco
2021	A*	`conf`	Faster Kernel Matrix Algebra via Density Estimation. ICML Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
2021	J	`jnl`	Faster Kernel Matrix Algebra via Density Estimation. CoRR Arturs Backurs, Piotr Indyk, Cameron Musco, Tal Wagner
2021	—	`conf`	Hutch++: Optimal Stochastic Trace Estimation. SOSA Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
2021	B	`conf`	Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. ALT Raghavendra Addanki, Andrew McGregor, Cameron Musco
2021	J	`jnl`	Local Edge Dynamics and Opinion Polarization. CoRR Nikita Bhalla, Adam Lechowicz, Cameron Musco
2021	A*	`conf`	On the Power of Edge Independent Graph Models. NeurIPS Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2021	J	`jnl`	On the Power of Edge Independent Graph Models. CoRR Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2021	A	`conf`	Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation. ITCS Cameron Musco, Christopher Musco, David P. Woodruff
2021	J	`jnl`	Sublinear Time Approximation of Text Similarity Matrices. CoRR Archan Ray, Nicholas Monath, Andrew McCallum, Cameron Musco
2021	J	`jnl`	Sublinear Time Eigenvalue Approximation via Random Sampling. CoRR Rajarshi Bhattacharjee, Cameron Musco, Archan Ray
2021	B	`conf`	Subspace Embeddings under Nonlinear Transformations. ALT Aarshvi Gajjar, Cameron Musco
2020	A*	`conf`	Efficient Intervention Design for Causal Discovery with Latents. ICML Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco
2020	J	`jnl`	Efficient Intervention Design for Causal Discovery with Latents. CoRR Raghavendra Addanki, Shiva Prasad Kasiviswanathan, Andrew McGregor, Cameron Musco
2020	J	`jnl`	Estimation of Shortest Path Covariance Matrices. CoRR Raj Kumar Maity, Cameron Musco
2020	A*	`conf`	Fast and Space Efficient Spectral Sparsification in Dynamic Streams. SODA Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri, Aaron Sidford, Jakab Tardos
2020	A*	`conf`	Fourier Sparse Leverage Scores and Approximate Kernel Learning. NeurIPS Tamás Erdélyi, Cameron Musco, Christopher Musco
2020	J	`jnl`	Fourier Sparse Leverage Scores and Approximate Kernel Learning. CoRR Tamás Erdélyi, Cameron Musco, Christopher Musco
2020	J	`jnl`	Hutch++: Optimal Stochastic Trace Estimation. CoRR Raphael A. Meyer, Cameron Musco, Christopher Musco, David P. Woodruff
2020	A	`conf`	Importance Sampling via Local Sensitivity. AISTATS Anant Raj, Cameron Musco, Lester Mackey
2020	A*	`conf`	InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. KDD Sudhanshu Chanpuriya, Cameron Musco
2020	J	`jnl`	InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity. CoRR Sudhanshu Chanpuriya, Cameron Musco
2020	J	`jnl`	Intervention Efficient Algorithms for Approximate Learning of Causal Graphs. CoRR Raghavendra Addanki, Andrew McGregor, Cameron Musco
2020	Misc	`conf`	Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers. ICASSP Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
2020	J	`jnl`	Model-specific Data Subsampling with Influence Functions. CoRR Anant Raj, Cameron Musco, Lester Mackey, Nicoló Fusi
2020	A*	`conf`	Near Optimal Linear Algebra in the Online and Sliding Window Models. FOCS Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2020	A*	`conf`	Node Embeddings and Exact Low-Rank Representations of Complex Networks. NeurIPS Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2020	J	`jnl`	Node Embeddings and Exact Low-Rank Representations of Complex Networks. CoRR Sudhanshu Chanpuriya, Cameron Musco, Konstantinos Sotiropoulos, Charalampos E. Tsourakakis
2020	J	`jnl`	Online Row Sampling. Theory Comput. Michael B. Cohen, Cameron Musco, Jakub Pachocki
2020	J	`jnl`	Projection-Cost-Preserving Sketches: Proof Strategies and Constructions. CoRR Cameron Musco, Christopher Musco
2020	A	`conf`	Random Sketching, Clustering, and Short-Term Memory in Spiking Neural Networks. ITCS Yael Hitron, Nancy A. Lynch, Cameron Musco, Merav Parter
2020	A*	`conf`	Sample Efficient Toeplitz Covariance Estimation. SODA Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
2020	A	`conf`	Spiking Neural Networks Through the Lens of Streaming Algorithms. DISC Yael Hitron, Cameron Musco, Merav Parter
2020	J	`jnl`	Spiking Neural Networks Through the Lens of Streaming Algorithms. CoRR Yael Hitron, Cameron Musco, Merav Parter
2020	J	`jnl`	Subspace Embeddings Under Nonlinear Transformations. CoRR Aarshvi Gajjar, Cameron Musco
2019	A*	`conf`	A universal sampling method for reconstructing signals with simple Fourier transforms. STOC Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2019	J	`jnl`	Faster Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Aida Mousavifar, Cameron Musco, Christopher Musco, Navid Nouri
2019	J	`jnl`	Importance Sampling via Local Sensitivity. CoRR Anant Raj, Cameron Musco, Lester Mackey
2019	A*	`conf`	Learning to Prune: Speeding up Repeated Computations. COLT Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	Learning to Prune: Speeding up Repeated Computations. CoRR Daniel Alabi, Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, Ellen Vitercik
2019	J	`jnl`	Low-Rank Approximation from Communication Complexity. CoRR Cameron Musco, Christopher Musco, David P. Woodruff
2019	J	`jnl`	Low-Rank Toeplitz Matrix Estimation via Random Ultra-Sparse Rulers. CoRR Hannah Lawrence, Jerry Li, Cameron Musco, Christopher Musco
2019	J	`jnl`	Sample Efficient Toeplitz Covariance Estimation. CoRR Yonina C. Eldar, Jerry Li, Cameron Musco, Christopher Musco
2019	A*	`conf`	Toward a Characterization of Loss Functions for Distribution Learning. NeurIPS Nika Haghtalab, Cameron Musco, Bo Waggoner
2019	J	`jnl`	Toward a Characterization of Loss Functions for Distribution Learning. CoRR Nika Haghtalab, Cameron Musco, Bo Waggoner
2019	J	`jnl`	Winner-Take-All Computation in Spiking Neural Networks. CoRR Nancy A. Lynch, Cameron Musco, Merav Parter
2018	J	`jnl`	A Basic Compositional Model for Spiking Neural Networks. CoRR Nancy A. Lynch, Cameron Musco
2018	J	`jnl`	A Universal Sampling Method for Reconstructing Signals with Simple Fourier Transforms. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A*	`conf`	Eigenvector Computation and Community Detection in Asynchronous Gossip Models. ICALP Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
2018	J	`jnl`	Eigenvector Computation and Community Detection in Asynchronous Gossip Models. CoRR Frederik Mallmann-Trenn, Cameron Musco, Christopher Musco
2018	A*	`conf`	Inferring Networks From Random Walk-Based Node Similarities. NeurIPS Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Babis Tsourakakis
2018	J	`jnl`	Learning Networks from Random Walk-Based Node Similarities. CoRR Jeremy G. Hoskins, Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2018	A*	`conf`	Minimizing Polarization and Disagreement in Social Networks. WWW Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2018	J	`jnl`	Near Optimal Linear Algebra in the Online and Sliding Window Models CoRR Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco, Jalaj Upadhyay, David P. Woodruff, Samson Zhou
2018	J	`jnl`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. CoRR Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2018	A	`conf`	Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness. ITCS Cameron Musco, Praneeth Netrapalli, Aaron Sidford, Shashanka Ubaru, David P. Woodruff
2018	A*	`conf`	Stability of the Lanczos Method for Matrix Function Approximation. SODA Cameron Musco, Christopher Musco, Aaron Sidford
2018	—	`—`	The power of randomized algorithms: from numerical linear algebra to biological systems. Cameron Musco
2017	J	`jnl`	Ant-inspired density estimation via random walks. Proc. Natl. Acad. Sci. USA Cameron Musco, Hsin-Hao Su, Nancy A. Lynch
2017	A	`conf`	Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks. ITCS Nancy A. Lynch, Cameron Musco, Merav Parter
2017	A*	`conf`	Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling. SODA Michael B. Cohen, Cameron Musco, Christopher Musco
2017	—	`conf`	Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? NIPS Cameron Musco, David P. Woodruff
2017	J	`jnl`	Is Input Sparsity Time Possible for Kernel Low-Rank Approximation? CoRR Cameron Musco, David P. Woodruff
2017	J	`jnl`	Minimizing Polarization and Disagreement in Social Networks. CoRR Cameron Musco, Christopher Musco, Charalampos E. Tsourakakis
2017	A	`conf`	Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks. DISC Nancy A. Lynch, Cameron Musco, Merav Parter
2017	J	`jnl`	Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks. CoRR Nancy A. Lynch, Cameron Musco, Merav Parter
2017	A*	`conf`	Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees. ICML Haim Avron, Michael Kapralov, Cameron Musco, Christopher Musco, Ameya Velingker, Amir Zandieh
2017	—	`conf`	Recursive Sampling for the Nystrom Method. NIPS Cameron Musco, Christopher Musco
2017	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. SIAM J. Comput. Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2017	J	`jnl`	Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness. CoRR Cameron Musco, Praneeth Netrapalli, Aaron Sidford, Shashanka Ubaru, David P. Woodruff
2017	J	`jnl`	Stability of the Lanczos Method for Matrix Function Approximation. CoRR Cameron Musco, Christopher Musco, Aaron Sidford
2017	A*	`conf`	Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices. FOCS Cameron Musco, David P. Woodruff
2017	J	`jnl`	Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices. CoRR Cameron Musco, David P. Woodruff
2016	J	`jnl`	Ant-Inspired Density Estimation via Random Walks. CoRR Cameron Musco, Hsin-Hao Su, Nancy A. Lynch
2016	A*	`conf`	Ant-Inspired Density Estimation via Random Walks: Extended Abstract. PODC Cameron Musco, Hsin-Hao Su, Nancy A. Lynch
2016	J	`jnl`	Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks. CoRR Nancy A. Lynch, Cameron Musco, Merav Parter
2016	A*	`conf`	Faster Eigenvector Computation via Shift-and-Invert Preconditioning. ICML Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford
2016	J	`jnl`	Faster Eigenvector Computation via Shift-and-Invert Preconditioning. CoRR Dan Garber, Elad Hazan, Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford
2016	—	`conf`	Online Row Sampling. APPROX-RANDOM Michael B. Cohen, Cameron Musco, Jakub Pachocki
2016	J	`jnl`	Online Row Sampling. CoRR Michael B. Cohen, Cameron Musco, Jakub Pachocki
2016	A*	`conf`	Principal Component Projection Without Principal Component Analysis. ICML Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
2016	J	`jnl`	Principal Component Projection Without Principal Component Analysis. CoRR Roy Frostig, Cameron Musco, Christopher Musco, Aaron Sidford
2016	J	`jnl`	Provably Useful Kernel Matrix Approximation in Linear Time. CoRR Cameron Musco, Christopher Musco
2015	A*	`conf`	Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. STOC Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu
2015	A*	`conf`	Distributed House-Hunting in Ant Colonies. PODC Mohsen Ghaffari, Cameron Musco, Tsvetomira Radeva, Nancy A. Lynch
2015	J	`jnl`	Distributed House-Hunting in Ant Colonies. CoRR Mohsen Ghaffari, Cameron Musco, Tsvetomira Radeva, Nancy A. Lynch
2015	—	`conf`	Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition. NIPS Cameron Musco, Christopher Musco
2015	J	`jnl`	Ridge Leverage Scores for Low-Rank Approximation. CoRR Michael B. Cohen, Cameron Musco, Christopher Musco
2015	J	`jnl`	Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation. CoRR Chi Jin, Sham M. Kakade, Cameron Musco, Praneeth Netrapalli, Aaron Sidford
2015	J	`jnl`	Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods. CoRR Cameron Musco, Christopher Musco
2015	A	`conf`	Uniform Sampling for Matrix Approximation. ITCS Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford
2014	J	`jnl`	Dimensionality Reduction for k-Means Clustering and Low Rank Approximation. CoRR Michael B. Cohen, Sam Elder, Cameron Musco, Christopher Musco, Madalina Persu
2014	A*	`conf`	Single Pass Spectral Sparsification in Dynamic Streams. FOCS Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	J	`jnl`	Single Pass Spectral Sparsification in Dynamic Streams. CoRR Michael Kapralov, Yin Tat Lee, Cameron Musco, Christopher Musco, Aaron Sidford
2014	J	`jnl`	Uniform Sampling for Matrix Approximation. CoRR Michael B. Cohen, Yin Tat Lee, Cameron Musco, Christopher Musco, Richard Peng, Aaron Sidford