Approximate Kernel PCA Using Random Features: Computational vs.
Statistical Trade-off

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Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off

20 June 2017

Bharath K. Sriperumbudur

Nicholas Sterge

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Papers citing "Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off"

11 / 11 papers shown

Title
Spectral Regularized Kernel Goodness-of-Fit Tests Omar Hagrass Bharath K. Sriperumbudur Bing Li 120 4 0 08 Aug 2023
Generalization Properties of Learning with Random Features Alessandro Rudi Lorenzo Rosasco MLT 68 331 0 14 Feb 2016
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 43 277 0 16 Jul 2015
Optimal Rates for Random Fourier Features Bharath K. Sriperumbudur Z. Szabó 75 130 0 06 Jun 2015
Randomized sketches for kernels: Fast and optimal non-parametric regression Yun Yang Mert Pilanci Martin J. Wainwright 82 174 0 25 Jan 2015
On the Sample Complexity of Subspace Learning Alessandro Rudi Guillermo D. Cañas Lorenzo Rosasco 55 28 0 21 Aug 2014
Randomized Nonlinear Component Analysis David Lopez-Paz S. Sra Alex Smola Zoubin Ghahramani Bernhard Schölkopf 134 176 0 01 Feb 2014
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 161 282 0 09 Aug 2012
Learning Sets with Separating Kernels Ernesto De Vito Lorenzo Rosasco A. Toigo 85 52 0 16 Apr 2012
Random Feature Maps for Dot Product Kernels Purushottam Kar H. Karnick 82 256 0 31 Jan 2012
Improved Bound for the Nystrom's Method and its Application to Kernel Classification Rong Jin Tianbao Yang M. Mahdavi Yu-Feng Li Zhi Zhou 95 61 0 09 Nov 2011