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Mark Tygert

Showing results (1-10 of 7) with videos related to

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Proceedings of the National Academy of Sciences of the United States of America|September 9, 2010
Statistical tests for whether a given set of independent, identically distributed draws comes from a specified probability densityMark Tygert
Proceedings of the National Academy of Sciences of the United States of America|September 10, 2008
A fast randomized algorithm for overdetermined linear least-squares regressionVladimir Rokhlin, Mark Tygert
Plos One|December 20, 2019
A hierarchical loss and its problems when classifying non-hierarchicallyCinna Wu, Mark Tygert, Yann LeCun
Advances in Computational Mathematics|September 6, 2021
Randomized algorithms for distributed computation of principal component analysis and singular value decompositionHuamin Li, Yuval Kluger, Mark Tygert
Proceedings of the National Academy of Sciences of the United States of America|December 7, 2007
Randomized algorithms for the low-rank approximation of matricesEdo Liberty, Franco Woolfe, Per-Gunnar Martinsson, et al.
Neural Computation|February 19, 2016
A Mathematical Motivation for Complex-Valued Convolutional NetworksMark Tygert, Joan Bruna, Soumith Chintala, et al.
ACM Transactions on Mathematical Software. Association for Computing Machinery|October 7, 2017
Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component AnalysisHuamin Li, George C Linderman, Arthur Szlam, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
Proceedings of the National Academy of Sciences of the United States of America|September 9, 2010
Statistical tests for whether a given set of independent, identically distributed draws comes from a specified probability densityMark Tygert
Proceedings of the National Academy of Sciences of the United States of America|September 10, 2008
A fast randomized algorithm for overdetermined linear least-squares regressionVladimir Rokhlin, Mark Tygert
Plos One|December 20, 2019
A hierarchical loss and its problems when classifying non-hierarchicallyCinna Wu, Mark Tygert, Yann LeCun
Advances in Computational Mathematics|September 6, 2021
Randomized algorithms for distributed computation of principal component analysis and singular value decompositionHuamin Li, Yuval Kluger, Mark Tygert
Proceedings of the National Academy of Sciences of the United States of America|December 7, 2007
Randomized algorithms for the low-rank approximation of matricesEdo Liberty, Franco Woolfe, Per-Gunnar Martinsson, et al.
Neural Computation|February 19, 2016
A Mathematical Motivation for Complex-Valued Convolutional NetworksMark Tygert, Joan Bruna, Soumith Chintala, et al.
ACM Transactions on Mathematical Software. Association for Computing Machinery|October 7, 2017
Algorithm 971: An Implementation of a Randomized Algorithm for Principal Component AnalysisHuamin Li, George C Linderman, Arthur Szlam, et al.
Pageof 1