Distributed Optimization with Arbitrary Local Solvers

13 December 2015

Papers citing "Distributed Optimization with Arbitrary Local Solvers"

44 / 44 papers shown

Title
Stochastic Channel-Based Federated Learning for Medical Data Privacy Preserving Rulin Shao Hongyu Hè Hui Liu Dianbo Liu FedML OOD 139 13 0 23 Oct 2019
AIDE: Fast and Communication Efficient Distributed Optimization Sashank J. Reddi Jakub Konecný Peter Richtárik Barnabás Póczós Alex Smola 47 151 0 24 Aug 2016
Distributed Inexact Damped Newton Method: Data Partitioning and Load-Balancing Chenxin Ma Martin Takáč 47 10 0 16 Mar 2016
Primal-Dual Rates and Certificates Celestine Mendler-Dünner Simone Forte Martin Takáč Martin Jaggi 62 60 0 16 Feb 2016
Importance Sampling for Minibatches Dominik Csiba Peter Richtárik 58 114 0 06 Feb 2016
L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework Virginia Smith Simone Forte Michael I. Jordan Martin Jaggi 117 28 0 13 Dec 2015
Federated Optimization:Distributed Optimization Beyond the Datacenter Jakub Konecný H. B. McMahan Daniel Ramage FedML 97 733 0 11 Nov 2015
Stop Wasting My Gradients: Practical SVRG Reza Babanezhad Mohamed Osama Ahmed Alim Virani Mark Schmidt Jakub Konecný Scott Sallinen 55 134 0 05 Nov 2015
Partitioning Data on Features or Samples in Communication-Efficient Distributed Optimization? Chenxin Ma Martin Takáč 78 11 0 22 Oct 2015
Distributed Mini-Batch SDCA Martin Takáč Peter Richtárik Nathan Srebro 54 50 0 29 Jul 2015
DUAL-LOCO: Distributing Statistical Estimation Using Random Projections C. Heinze Brian McWilliams N. Meinshausen 97 37 0 08 Jun 2015
Primal Method for ERM with Flexible Mini-batching Schemes and Non-convex Losses Dominik Csiba Peter Richtárik 65 23 0 07 Jun 2015
Communication Complexity of Distributed Convex Learning and Optimization Yossi Arjevani Ohad Shamir 74 207 0 05 Jun 2015
Domain-Adversarial Training of Neural Networks Yaroslav Ganin E. Ustinova Hana Ajakan Pascal Germain Hugo Larochelle François Laviolette M. Marchand Victor Lempitsky GAN OOD 347 9,418 0 28 May 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 92 273 0 16 Apr 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 87 97 0 27 Feb 2015
SDCA without Duality Shai Shalev-Shwartz 46 47 0 22 Feb 2015
Adding vs. Averaging in Distributed Primal-Dual Optimization Chenxin Ma Virginia Smith Martin Jaggi Michael I. Jordan Peter Richtárik Martin Takáč FedML 86 176 0 12 Feb 2015
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq ODL 69 99 0 08 Feb 2015
Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation Zheng Qu Peter Richtárik 144 83 0 27 Dec 2014
Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity Zheng Qu Peter Richtárik 50 130 0 27 Dec 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 67 353 0 04 Sep 2014
Finito: A Faster, Permutable Incremental Gradient Method for Big Data Problems Aaron Defazio T. Caetano Justin Domke 92 169 0 10 Jul 2014
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 110 1,817 0 01 Jul 2014
LOCO: Distributing Ridge Regression with Random Projections C. Heinze Brian McWilliams N. Meinshausen Gabriel Krummenacher 69 34 0 13 Jun 2014
Fast Distributed Coordinate Descent for Non-Strongly Convex Losses Olivier Fercoq Zheng Qu Peter Richtárik Martin Takáč 57 59 0 21 May 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 140 738 0 19 Mar 2014
A Stochastic Quasi-Newton Method for Large-Scale Optimization R. Byrd Samantha Hansen J. Nocedal Y. Singer ODL 87 471 0 27 Jan 2014
Communication Efficient Distributed Optimization using an Approximate Newton-type Method Ohad Shamir Nathan Srebro Tong Zhang 70 554 0 30 Dec 2013
Accelerated, Parallel and Proximal Coordinate Descent Olivier Fercoq Peter Richtárik 64 372 0 20 Dec 2013
Semi-Stochastic Gradient Descent Methods Jakub Konecný Peter Richtárik ODL 97 238 0 05 Dec 2013
Analysis of Distributed Stochastic Dual Coordinate Ascent Tianbao Yang Shenghuo Zhu Rong Jin Yuanqing Lin 54 19 0 04 Dec 2013
Stochastic Gradient Descent, Weighted Sampling, and the Randomized Kaczmarz algorithm Deanna Needell Nathan Srebro Rachel A. Ward 104 551 0 21 Oct 2013
On Optimal Probabilities in Stochastic Coordinate Descent Methods Peter Richtárik Martin Takáč 65 131 0 13 Oct 2013
Distributed Coordinate Descent Method for Learning with Big Data Peter Richtárik Martin Takáč 155 254 0 08 Oct 2013
Minimizing Finite Sums with the Stochastic Average Gradient Mark Schmidt Nicolas Le Roux Francis R. Bach 257 1,246 0 10 Sep 2013
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang ODL 84 462 0 10 Sep 2013
Separable Approximations and Decomposition Methods for the Augmented Lagrangian R. Tappenden Peter Richtárik Burak Büke 44 41 0 30 Aug 2013
Inexact Coordinate Descent: Complexity and Preconditioning R. Tappenden Peter Richtárik J. Gondzio 62 100 0 19 Apr 2013
Mini-Batch Primal and Dual Methods for SVMs Martin Takáč A. Bijral Peter Richtárik Nathan Srebro 57 195 0 10 Mar 2013
Parallel Coordinate Descent Methods for Big Data Optimization Peter Richtárik Martin Takáč 94 487 0 04 Dec 2012
Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang 117 1,031 0 10 Sep 2012
Iteration Complexity of Randomized Block-Coordinate Descent Methods for Minimizing a Composite Function Peter Richtárik Martin Takáč 86 769 0 14 Jul 2011
HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright 146 2,272 0 28 Jun 2011