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Compressive Statistical Learning with Random Feature Moments

22 June 2017

Rémi Gribonval

Papers citing "Compressive Statistical Learning with Random Feature Moments"

38 / 38 papers shown

Title
Statistical Learning Guarantees for Compressive Clustering and Compressive Mixture Modeling Rémi Gribonval Gilles Blanchard Nicolas Keriven Y. Traonmilin 22 14 0 17 Apr 2020
Gain with no Pain: Efficient Kernel-PCA by Nyström Sampling Nicholas Sterge Bharath K. Sriperumbudur Lorenzo Rosasco Alessandro Rudi 103 8 0 11 Jul 2019
On the Inductive Bias of Neural Tangent Kernels A. Bietti Julien Mairal 91 259 0 29 May 2019
$Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features$ Streaming Kernel PCA with $\tilde{O}(\sqrt{n})$ Random Features Enayat Ullah Poorya Mianjy T. V. Marinov R. Arora 106 22 0 02 Aug 2018
Neural Tangent Kernel: Convergence and Generalization in Neural Networks Arthur Jacot Franck Gabriel Clément Hongler 273 3,219 0 20 Jun 2018
Entropy and mutual information in models of deep neural networks Marylou Gabrié Andre Manoel Clément Luneau Jean Barbier N. Macris Florent Krzakala Lenka Zdeborová 71 180 0 24 May 2018
Demystifying MMD GANs Mikolaj Binkowski Danica J. Sutherland Michael Arbel Arthur Gretton EGVM 174 1,500 0 04 Jan 2018
Approximate Kernel PCA Using Random Features: Computational vs. Statistical Trade-off Bharath K. Sriperumbudur Nicholas Sterge 51 22 0 20 Jun 2017
Towards Understanding the Invertibility of Convolutional Neural Networks A. Gilbert Yi Zhang Kibok Lee Y. Zhang Honglak Lee 65 64 0 24 May 2017
Training Gaussian Mixture Models at Scale via Coresets Mario Lucic Matthew Faulkner Andreas Krause Dan Feldman 70 101 0 23 Mar 2017
Opening the Black Box of Deep Neural Networks via Information Ravid Shwartz-Ziv Naftali Tishby AI4CE 107 1,416 0 02 Mar 2017
Compressive K-means Nicolas Keriven Nicolas M Tremblay Y. Traonmilin Rémi Gribonval 74 53 0 27 Oct 2016
Structured adaptive and random spinners for fast machine learning computations Mariusz Bojarski A. Choromańska K. Choromanski Francois Fagan Cédric Gouy-Pailler Anne Morvan Nourhan Sakr Tamás Sarlós Jamal Atif 69 35 0 19 Oct 2016
Non-asymptotic upper bounds for the reconstruction error of PCA M. Reiß Martin Wahl 71 56 0 13 Sep 2016
Sketching for Large-Scale Learning of Mixture Models Nicolas Keriven Anthony Bourrier Rémi Gribonval Patrick Pérez 65 75 0 09 Jun 2016
TripleSpin - a generic compact paradigm for fast machine learning computations K. Choromanski Francois Fagan Cédric Gouy-Pailler Anne Morvan Vikas Sindhwani Jamal Atif 83 7 0 29 May 2016
Streaming Kernel Principal Component Analysis Mina Ghashami Daniel J. Perry J. M. Phillips 43 38 0 16 Dec 2015
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 45 277 0 16 Jul 2015
Optimal Rates for Random Fourier Features Bharath K. Sriperumbudur Z. Szabó 88 130 0 06 Jun 2015
Deep Neural Networks with Random Gaussian Weights: A Universal Classification Strategy? Raja Giryes Guillermo Sapiro A. Bronstein 109 187 0 30 Apr 2015
Generative Moment Matching Networks Yujia Li Kevin Swersky R. Zemel OOD GAN 116 847 0 10 Feb 2015
Exact solutions to Super Resolution on semi-algebraic domains in higher dimensions Yohann De Castro Fabrice Gamboa Didier Henrion J. Lasserre 49 75 0 09 Feb 2015
The Fast Convergence of Incremental PCA Akshay Balsubramani S. Dasgupta Y. Freund 79 143 0 15 Jan 2015
Fastfood: Approximate Kernel Expansions in Loglinear Time Quoc V. Le Tamás Sarlós Alex Smola 95 444 0 13 Aug 2014
Dimensionality reduction with subgaussian matrices: a unified theory S. Dirksen 87 82 0 17 Feb 2014
Signal Recovery from Pooling Representations Joan Bruna Arthur Szlam Yann LeCun 91 96 0 16 Nov 2013
The More, the Merrier: the Blessing of Dimensionality for Learning Large Gaussian Mixtures Joseph Anderson M. Belkin Navin Goyal Luis Rademacher James R. Voss 136 93 0 12 Nov 2013
A Two-round Variant of EM for Gaussian Mixtures S. Dasgupta Leonard J. Schulman 157 167 0 16 Jan 2013
Privacy Aware Learning John C. Duchi Michael I. Jordan Martin J. Wainwright 175 290 0 07 Oct 2012
Learning mixtures of spherical Gaussians: moment methods and spectral decompositions Daniel J. Hsu Sham Kakade 227 326 0 25 Jun 2012
Fast rates for empirical vector quantization Clément Levrard MQ 68 40 0 29 Jan 2012
A Unified Framework for Approximating and Clustering Data Dan Feldman M. Langberg 161 458 0 07 Jun 2011
Polynomial Learning of Distribution Families M. Belkin Kaushik Sinha 399 226 0 27 Apr 2010
Online Learning for Matrix Factorization and Sparse Coding Julien Mairal Francis R. Bach Jean Ponce Guillermo Sapiro 157 2,616 0 01 Aug 2009
Hilbert space embeddings and metrics on probability measures Bharath K. Sriperumbudur Arthur Gretton Kenji Fukumizu Bernhard Schölkopf Gert R. G. Lanckriet 217 747 0 30 Jul 2009
Adaptive Dantzig density estimation Karine Bertin E. L. Pennec Vincent Rivoirard 174 45 0 06 May 2009
A Kernel Method for the Two-Sample Problem Arthur Gretton Karsten Borgwardt Malte J. Rasch Bernhard Schölkopf Alex Smola 233 2,365 0 15 May 2008
Online EM Algorithm for Latent Data Models Olivier Cappé Eric Moulines 147 482 0 27 Dec 2007