Cameron Musco

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Christopher MuscoAssistant Professor, New York UniversityGeverifieerd e-mailadres voor nyu.edu
Aaron SidfordStanford UniversityGeverifieerd e-mailadres voor stanford.edu
David WoodruffProfessor of Computer Science, Carnegie Mellon UniversityGeverifieerd e-mailadres voor cs.cmu.edu
Nancy LynchProfessor of EECS, MITGeverifieerd e-mailadres voor csail.mit.edu
Michael B. CohenGraduate Student in Computer Science, MITGeverifieerd e-mailadres voor mit.edu
Praneeth NetrapalliGoogle ResearchGeverifieerd e-mailadres voor google.com
Yin Tat LeePaul G. Allen School of Computer Science & Engineering, University of WashingtonGeverifieerd e-mailadres voor uw.edu
Chi JinAssistant Professor, Princeton UniversityGeverifieerd e-mailadres voor princeton.edu
Haim AvronAssociate Professor, Tel Aviv UniversityGeverifieerd e-mailadres voor tauex.tau.ac.il
Richard PengUniversity of WaterlooGeverifieerd e-mailadres voor uwaterloo.ca
Elad HazanProfessor at Princeton University and Director Google AI PrincetonGeverifieerd e-mailadres voor princeton.edu
Dan GarberAssociate Professor at Technion - Israel Institute of TechnologyGeverifieerd e-mailadres voor technion.ac.il
Tsvetomira RadevaGrad Student, MITGeverifieerd e-mailadres voor csail.mit.edu
Shashanka UbaruIBM ResearchGeverifieerd e-mailadres voor umn.edu
Roy FrostigResearch scientist, Google Research, Brain teamGeverifieerd e-mailadres voor cs.stanford.edu
Sham M KakadeHarvard UniversityGeverifieerd e-mailadres voor seas.harvard.edu

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Cameron Musco

Assistant Professor, University of Massachusetts Amherst

Geverifieerd e-mailadres voor cs.umass.edu - Homepage

Algorithms Data Science Linear Algebraic Computation Biological Algorithms


Titel Sorteren op citaties Sorteren op jaar Sorteren op titel	Geciteerd door Geciteerd door	Jaar
Dimensionality reduction for k-means clustering and low rank approximation MB Cohen, S Elder, C Musco, C Musco, M Persu Proceedings of the forty-seventh annual ACM symposium on Theory of computing …, 2015	384	2015
Randomized block krylov methods for stronger and faster approximate singular value decomposition C Musco, C Musco Advances in neural information processing systems 28, 2015	297	2015
Uniform sampling for matrix approximation MB Cohen, YT Lee, C Musco, C Musco, R Peng, A Sidford Proceedings of the 2015 Conference on Innovations in Theoretical Computer …, 2015	235	2015
Recursive Sampling for the Nyström Method C Musco, C Musco arXiv preprint arXiv:1605.07583, 2016	204	2016
Random Fourier features for kernel ridge regression: Approximation bounds and statistical guarantees H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh International conference on machine learning, 253-262, 2017	166	2017
Single pass spectral sparsification in dynamic streams M Kapralov, YT Lee, C Musco, C Musco, A Sidford Foundations of Computer Science (FOCS), 2014 IEEE 55th Annual Symposium on …, 2014	160	2014
Input sparsity time low-rank approximation via ridge leverage score sampling MB Cohen, C Musco, C Musco Proceedings of the Twenty-Eighth Annual ACM-SIAM Symposium on Discrete …, 2017	149*	2017
Minimizing polarization and disagreement in social networks C Musco, C Musco, CE Tsourakakis Proceedings of the 2018 world wide web conference, 369-378, 2018	126	2018
Faster eigenvector computation via shift-and-invert preconditioning D Garber, E Hazan, C Jin, C Musco, P Netrapalli, A Sidford International Conference on Machine Learning, 2626-2634, 2016	120*	2016
Hutch++: Optimal stochastic trace estimation RA Meyer, C Musco, C Musco, DP Woodruff Symposium on Simplicity in Algorithms (SOSA), 142-155, 2021	84	2021
Online row sampling MB Cohen, C Musco, J Pachocki Theory of Computing 16 (1), 1-25, 2020	67*	2020
Sublinear time low-rank approximation of positive semidefinite matrices C Musco, DP Woodruff 2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS …, 2017	54	2017
Near optimal linear algebra in the online and sliding window models SZ Vladimir Braverman, Petros Drineas, Cameron Musco, Christopher Musco ... arXiv preprint arXiv:1805.03765, 2018	52*	2018
Stability of the Lanczos method for matrix function approximation C Musco, C Musco, A Sidford Proceedings of the Twenty-Ninth Annual ACM-SIAM Symposium on Discrete …, 2018	45	2018
Ant-inspired density estimation via random walks C Musco, HH Su, N Lynch Proceedings of the 2016 ACM Symposium on Principles of Distributed Computing …, 2016	41	2016
Spectrum approximation beyond fast matrix multiplication: Algorithms and hardness C Musco, P Netrapalli, A Sidford, S Ubaru, DP Woodruff arXiv preprint arXiv:1704.04163, 2017	37	2017
Node embeddings and exact low-rank representations of complex networks S Chanpuriya, C Musco, K Sotiropoulos, C Tsourakakis Advances in neural information processing systems 33, 13185-13198, 2020	35	2020
A universal sampling method for reconstructing signals with simple fourier transforms H Avron, M Kapralov, C Musco, C Musco, A Velingker, A Zandieh Proceedings of the 51st Annual ACM SIGACT Symposium on Theory of Computing …, 2019	35	2019
Principal component projection without principal component analysis R Frostig, C Musco, C Musco, A Sidford International Conference on Machine Learning, 2349-2357, 2016	35	2016
Infinitewalk: Deep network embeddings as laplacian embeddings with a nonlinearity S Chanpuriya, C Musco Proceedings of the 26th ACM SIGKDD International Conference on Knowledge …, 2020	33	2020

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