Cameron Musco

发表

Robust Shift-and-Invert Preconditioning: Faster and More Sample Efficient Algorithms for Eigenvector Computation pdf

Sham M. Kakade, Praneeth Netrapalli, Aaron Sidford, 2015, ArXiv.

Faster Eigenvector Computation via Shift-and-Invert Preconditioning

Sham M. Kakade, Praneeth Netrapalli, Elad Hazan, 2016, ICML.

Randomized Block Krylov Methods for Stronger and Faster Approximate Singular Value Decomposition

Cameron Musco, Christopher Musco, Cameron Musco, 2015, NIPS.

Dimensionality Reduction for k-Means Clustering and Low Rank Approximation

Michael B. Cohen, Cameron Musco, Christopher Musco, 2014, STOC.

Stronger and Faster Approximate Singular Value Decomposition via the Block Lanczos Method

Cameron Musco, C. Musco, 2015 .

Principal Component Projection Without Principal Component Analysis

Aaron Sidford, Cameron Musco, Christopher Musco, 2016, ICML.

Single Pass Spectral Sparsification in Dynamic Streams

Yin Tat Lee, Aaron Sidford, Cameron Musco, 2014, 2014 IEEE 55th Annual Symposium on Foundations of Computer Science.

Spectrum Approximation Beyond Fast Matrix Multiplication: Algorithms and Hardness

David P. Woodruff, Praneeth Netrapalli, Aaron Sidford, 2017, ITCS.

Uniform Sampling for Matrix Approximation

Richard Peng, Yin Tat Lee, Michael B. Cohen, 2014, ITCS.

Subspace Scores for Feature Selection in Computer Vision

Cameron Musco, 2015 .

Sublinear Time Approximation of Text Similarity Matrices

A. McCallum, Cameron Musco, Archan Ray, 2021, AAAI.

Recursive Sampling for the Nystr\"om Method

Cameron Musco, C. Musco, 2016, NIPS 2017.

Fast and Space Efficient Spectral Sparsification in Dynamic Streams

Aaron Sidford, Cameron Musco, Christopher Musco, 2020, SODA.

Simplified Graph Convolution with Heterophily

Cameron Musco, Sudhanshu Chanpuriya, Cameron Musco, 2022, NeurIPS.

Error bounds for Lanczos-based matrix function approximation

A. Greenbaum, Cameron Musco, C. Musco, 2021, SIAM J. Matrix Anal. Appl..

Sublinear Time Eigenvalue Approximation via Random Sampling

Cameron Musco, Archan Ray, Rajarshi Bhattacharjee, 2021, ArXiv.

Non-Adaptive Edge Counting and Sampling via Bipartite Independent Set Queries

Cameron Musco, A. Mcgregor, Raghavendra Addanki, 2022, ESA.

Near Optimal Linear Algebra in the Online and Sliding Window Models

David P. Woodruff, Cameron Musco, V. Braverman, 2018, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

Near Optimal Linear Algebra in the Online and Sliding Window Models

David P. Woodruff, Cameron Musco, V. Braverman, 2018, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

Sublinear Time Eigenvalue Approximation via Random Sampling

Cameron Musco, Archan Ray, Rajarshi Bhattacharjee, 2021, ICALP.

Low-memory Krylov subspace methods for optimal rational matrix function approximation

A. Greenbaum, Cameron Musco, C. Musco, 2022, ArXiv.

Exact Representation of Sparse Networks with Symmetric Nonnegative Embeddings

Ryan A. Rossi, Anup B. Rao, Tung Mai, 2021, 2111.03030.

Sample Constrained Treatment Effect Estimation

Anup B. Rao, Tung Mai, Cameron Musco, 2022, NeurIPS.

Fast Approximation of Maximum Flow using Electrical Flows

D. Spielman, Cameron Musco, 2011 .

Active Linear Regression for ℓp Norms and Beyond

David P. Woodruff, Cameron Musco, C. Musco, 2022, 2022 IEEE 63rd Annual Symposium on Foundations of Computer Science (FOCS).

Weighted Minwise Hashing Beats Linear Sketching for Inner Product Estimation

H. Zhang, Cameron Musco, C. Musco, 2023, ArXiv.

Winner-Take-All Computation in Spiking Neural Networks pdf

Nancy A. Lynch, Merav Parter, Cameron Musco, 2019, ArXiv.

The power of randomized algorithms: from numerical linear algebra to biological systems

Cameron Musco, Cameron Musco, 2018 .

A universal sampling method for reconstructing signals with simple Fourier transforms

Ameya Velingker, Haim Avron, Cameron Musco, 2018, STOC.

Spiking Neural Networks Through the Lens of Streaming Algorithms

Merav Parter, Cameron Musco, Yael Hitron, 2020, DISC.

Random Sketching, Clustering, and Short-Term Memory in Spiking Neural Networks

Merav Parter, Cameron Musco, Nancy Lynch, 2020, ITCS.

Faster Spectral Sparsification in Dynamic Streams pdf

Cameron Musco, Christopher Musco, Mikhail Kapralov, 2019, ArXiv.

Is Input Sparsity Time Possible for Kernel Low-Rank Approximation?

David P. Woodruff, Cameron Musco, Cameron Musco, 2017, NIPS.

An Interpretable Graph Generative Model with Heterophily pdf

Ryan A. Rossi, Tung Mai, Nedim Lipka, 2021, ArXiv.

Toeplitz Low-Rank Approximation with Sublinear Query Complexity

Cameron Musco, Michael Kapralov, Hannah Lawrence, 2022, SODA.

Estimation of Shortest Path Covariance Matrices pdf

Raj Kumar Maity, Cameron Musco, Cameron Musco, 2020, ArXiv.

Neuro-RAM Unit with Applications to Similarity Testing and Compression in Spiking Neural Networks

Nancy A. Lynch, Merav Parter, Cameron Musco, 2017, DISC.

Random Fourier Features for Kernel Ridge Regression: Approximation Bounds and Statistical Guarantees pdf

Ameya Velingker, Haim Avron, Cameron Musco, 2018, ICML.

Recursive Sampling for the Nystrom Method

Cameron Musco, Christopher Musco, Cameron Musco, 2016, NIPS.

Subspace Embeddings Under Nonlinear Transformations pdf

Cameron Musco, Aarshvi Gajjar, Cameron Musco, 2020, ALT.

Hutch++: Optimal Stochastic Trace Estimation pdf

David P. Woodruff, Cameron Musco, Christopher Musco, 2020, SOSA.

Computational Tradeoffs in Biological Neural Networks: Self-Stabilizing Winner-Take-All Networks pdf

Nancy A. Lynch, Merav Parter, Cameron Musco, 2016, ITCS.

Toward a Characterization of Loss Functions for Distribution Learning

Bo Waggoner, Cameron Musco, Nika Haghtalab, 2019, NeurIPS.

Single Pass Spectral Sparsification in Dynamic Streams

Yin Tat Lee, Aaron Sidford, Cameron Musco, 2014, 2014 IEEE 55th Annual Symposium on Foundations of Computer Science.

Fast Regression for Structured Inputs

David P. Woodruff, Cameron Musco, C. Musco, 2022, ICLR.

Near Optimal Linear Algebra in the Online and Sliding Window Models

David P. Woodruff, Cameron Musco, V. Braverman, 2018, 2020 IEEE 61st Annual Symposium on Foundations of Computer Science (FOCS).

Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling

Michael B. Cohen, Cameron Musco, Christopher Musco, 2015, SODA.

Efficient Intervention Design for Causal Discovery with Latents

Cameron Musco, S. Kasiviswanathan, A. Mcgregor, 2020, ICML.

Minimizing Polarization and Disagreement in Social Networks

Charalampos E. Tsourakakis, Cameron Musco, Christopher Musco, 2017, WWW.

Inferring Networks From Random Walk-Based Node Similarities

Jeremy G. Hoskins, Cameron Musco, Christopher Musco, 2018, NeurIPS.

Stability of the Lanczos Method for Matrix Function Approximation pdf

Aaron Sidford, Cameron Musco, Christopher Musco, 2017, SODA.

Near-Optimality Guarantees for Approximating Rational Matrix Functions by the Lanczos Method

A. Greenbaum, Cameron Musco, C. Musco, 2023, ArXiv.

Low-memory Krylov subspace methods for optimal rational matrix function approximation

A. Greenbaum, Cameron Musco, C. Musco, 2022, SIAM Journal on Matrix Analysis and Applications.

On the Unreasonable Effectiveness of Single Vector Krylov Methods for Low-Rank Approximation

Cameron Musco, C. Musco, R. A. Meyer, 2023, ArXiv.

Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices

David P. Woodruff, Cameron Musco, Cameron Musco, 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

Local Edge Dynamics and Opinion Polarization

Cameron Musco, Adam Lechowicz, Nikita Bhalla, 2021, WSDM.

Online Row Sampling

Jakub W. Pachocki, Michael B. Cohen, Cameron Musco, 2016, APPROX-RANDOM.

Simple Heuristics Yield Provable Algorithms for Masked Low-Rank Approximation

David P. Woodruff, Cameron Musco, Christopher Musco, 2020, ITCS.

A Basic Compositional Model for Spiking Neural Networks pdf

Nancy A. Lynch, Cameron Musco, N. Lynch, 2018, A Journey from Process Algebra via Timed Automata to Model Learning.

Universal Matrix Sparsifiers and Fast Deterministic Algorithms for Linear Algebra

David P. Woodruff, Cameron Musco, Archan Ray, 2023, ArXiv.

Fourier Sparse Leverage Scores and Approximate Kernel Learning

Cameron Musco, C. Musco, T. Erd'elyi, 2020, NeurIPS.

Node Embeddings and Exact Low-Rank Representations of Complex Networks

Charalampos E. Tsourakakis, Cameron Musco, Sudhanshu Chanpuriya, 2020, NeurIPS.

Optimal Sketching Bounds for Sparse Linear Regression

David P. Woodruff, Anup B. Rao, Tung Mai, 2023, AISTATS.

Coresets for Classification - Simplified and Strengthened

Anup B. Rao, Tung Mai, Cameron Musco, 2021, NeurIPS.

Faster Kernel Matrix Algebra via Density Estimation

P. Indyk, Cameron Musco, A. Backurs, 2021, ICML.

Sublinear Time Low-Rank Approximation of Positive Semidefinite Matrices

David P. Woodruff, Cameron Musco, 2017, 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS).

DeepWalking Backwards: From Embeddings Back to Graphs

Charalampos E. Tsourakakis, Cameron Musco, Sudhanshu Chanpuriya, 2021, ICML.

InfiniteWalk: Deep Network Embeddings as Laplacian Embeddings with a Nonlinearity

Cameron Musco, Sudhanshu Chanpuriya, Cameron Musco, 2020, KDD.

Dimensionality reduction for k-means clustering

Cameron Musco, Cameron Musco, 2015 .

Projection-Cost-Preserving Sketches: Proof Strategies and Constructions pdf

Cameron Musco, Christopher Musco, Cameron Musco, 2020, ArXiv.

Sample Efficient Toeplitz Covariance Estimation

Yonina C. Eldar, Jerry Li, Cameron Musco, 2019, SODA.

Low-Rank Approximation from Communication Complexity pdf

David P. Woodruff, Cameron Musco, Christopher Musco, 2019, ArXiv.

Provably Useful Kernel Matrix Approximation in Linear Time pdf

Cameron Musco, Christopher Musco, Cameron Musco, 2016, ArXiv.

Stronger Approximate Singular Value Decomposition via the Block Lanczos and Power Methods pdf

Cameron Musco, Christopher Musco, Cameron Musco, 2015, ArXiv.

Intervention Efficient Algorithms for Approximate Learning of Causal Graphs pdf

Andrew McGregor, Raghavendra Addanki, Cameron Musco, 2020, ALT.

Faster Kernel Interpolation for Gaussian Processes pdf

Daniel Sheldon, Cameron Musco, Mohit Yadav, 2021, AISTATS.

On the Power of Edge Independent Graph Models pdf

Charalampos E. Tsourakakis, Cameron Musco, Sudhanshu Chanpuriya, 2021, NeurIPS.

Distributed House-Hunting in Ant Colonies

Nancy A. Lynch, Tsvetomira Radeva, Mohsen Ghaffari, 2015, PODC.

Ant-Inspired Density Estimation via Random Walks: Extended Abstract

Nancy A. Lynch, Hsin-Hao Su, Cameron Musco, 2016, PODC.

Ant-inspired density estimation via random walks

Nancy A. Lynch, Hsin-Hao Su, Cameron Musco, 2016, Proceedings of the National Academy of Sciences.

No-regret Algorithms for Fair Resource Allocation

Cameron Musco, M. Hajiesmaili, Rajarshi Bhattacharjee, 2023, NeurIPS.

Learning to Prune: Speeding up Repeated Computations pdf

Adam Tauman Kalai, Christos Tzamos, Katrina Ligett, 2019, COLT.

Faster Eigenvector Computation via Shift-and-Invert Preconditioning

S. Kakade, Elad Hazan, Chi Jin, 2016, ICML.

Input Sparsity Time Low-rank Approximation via Ridge Leverage Score Sampling

Michael B. Cohen, Cameron Musco, C. Musco, 2015, SODA.

Learning Networks from Random Walk-Based Node Similarities pdf

Charalampos E. Tsourakakis, Jeremy G. Hoskins, Cameron Musco, 2018, ArXiv.

Low-Rank Toeplitz Matrix Estimation Via Random Ultra-Sparse Rulers

Cameron Musco, Hannah Lawrence, Jerry Li, 2019, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Near-Linear Sample Complexity for $L_p$ Polynomial Regression

David P. Woodruff, Cameron Musco, C. Musco, 2022, 2211.06790.

Near-Optimal Approximation of Matrix Functions by the Lanczos Method

A. Greenbaum, Cameron Musco, Tyler Chen, 2023, 2303.03358.