Large Scale Kernel Learning using Block Coordinate Descent

Large Scale Kernel Learning using Block Coordinate Descent

17 February 2016

Stephen Tu

Rebecca Roelofs

Shivaram Venkataraman

Benjamin Recht

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Papers citing "Large Scale Kernel Learning using Block Coordinate Descent"

16 / 16 papers shown

Title
Joker: Joint Optimization Framework for Lightweight Kernel Machines Junhong Zhang Zhihui Lai 48 0 0 23 May 2025
Supervised Kernel Thinning Albert Gong Kyuseong Choi Raaz Dwivedi 155 0 0 17 Oct 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes J. Lin Shreyas Padhy Bruno Mlodozeniec Javier Antorán José Miguel Hernández-Lobato 69 3 0 28 May 2024
Less is More: Nyström Computational Regularization Alessandro Rudi Raffaello Camoriano Lorenzo Rosasco 43 277 0 16 Jul 2015
Adding vs. Averaging in Distributed Primal-Dual Optimization Chenxin Ma Virginia Smith Martin Jaggi Michael I. Jordan Peter Richtárik Martin Takáč FedML 99 177 0 12 Feb 2015
An Introduction to Matrix Concentration Inequalities J. Tropp 168 1,150 0 07 Jan 2015
Fast Randomized Kernel Methods With Statistical Guarantees A. Alaoui Michael W. Mahoney 85 90 0 02 Nov 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 91 353 0 04 Sep 2014
Distributed Coordinate Descent Method for Learning with Big Data Peter Richtárik Martin Takáč 184 255 0 08 Oct 2013
Least Squares Revisited: Scalable Approaches for Multi-class Prediction Alekh Agarwal Sham Kakade Nikos Karampatziakis Le Song Gregory Valiant 95 29 0 07 Oct 2013
Revisiting the Nystrom Method for Improved Large-Scale Machine Learning Alex Gittens Michael W. Mahoney 118 415 0 07 Mar 2013
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 184 1,033 0 10 Sep 2012
Sharp analysis of low-rank kernel matrix approximations Francis R. Bach 161 282 0 09 Aug 2012
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 198 2,273 0 28 Jun 2011
Distributed Delayed Stochastic Optimization Alekh Agarwal John C. Duchi 125 627 0 28 Apr 2011
Feature Hashing for Large Scale Multitask Learning Kilian Q. Weinberger A. Dasgupta Josh Attenberg John Langford Alex Smola 119 1,023 0 12 Feb 2009

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