Parallel Coordinate Descent Methods for Big Data Optimization

4 December 2012

Papers citing "Parallel Coordinate Descent Methods for Big Data Optimization"

50 / 52 papers shown

Title
Randomized Block-Coordinate Optimistic Gradient Algorithms for Root-Finding Problems Quoc Tran-Dinh Yang Luo 97 6 0 28 Jan 2025
A Mirror Descent-Based Algorithm for Corruption-Tolerant Distributed Gradient Descent Shuche Wang Vincent Y. F. Tan FedML OOD 49 1 0 19 Jul 2024
Demystifying SGD with Doubly Stochastic Gradients Kyurae Kim Joohwan Ko Yian Ma Jacob R. Gardner 53 0 0 03 Jun 2024
Adaptive Consensus: A network pruning approach for decentralized optimization S. Shah A. Berahas Raghu Bollapragada 22 2 0 06 Sep 2023
Laplacian-based Semi-Supervised Learning in Multilayer Hypergraphs by Coordinate Descent Sara Venturini Andrea Cristofari Francesco Rinaldi Francesco Tudisco 39 2 0 28 Jan 2023
FedADMM: A Federated Primal-Dual Algorithm Allowing Partial Participation Han Wang Siddartha Marella James Anderson FedML 14 39 0 28 Mar 2022
A dual approach for federated learning Zhenan Fan Huang Fang M. Friedlander FedML 18 3 0 26 Jan 2022
Cyclic Coordinate Dual Averaging with Extrapolation Chaobing Song Jelena Diakonikolas 27 6 0 26 Feb 2021
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
On the Convergence of SGD with Biased Gradients Ahmad Ajalloeian Sebastian U. Stich 6 83 0 31 Jul 2020
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm Majid Jahani M. Nazari R. Tappenden A. Berahas Martin Takávc ODL 11 10 0 06 Jun 2020
Columnwise Element Selection for Computationally Efficient Nonnegative Coupled Matrix Tensor Factorization Thirunavukarasu Balasubramaniam R. Nayak Chau Yuen 13 7 0 07 Mar 2020
Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 27 4 0 13 Feb 2020
Convergence Analysis of Block Coordinate Algorithms with Determinantal Sampling Mojmír Mutný Michal Derezinski Andreas Krause 38 20 0 25 Oct 2019
99% of Distributed Optimization is a Waste of Time: The Issue and How to Fix it Konstantin Mishchenko Filip Hanzely Peter Richtárik 16 13 0 27 Jan 2019
Accelerated Decentralized Optimization with Local Updates for Smooth and Strongly Convex Objectives Hadrien Hendrikx Francis R. Bach Laurent Massoulié 13 42 0 05 Oct 2018
Algorithms for solving optimization problems arising from deep neural net models: smooth problems Vyacheslav Kungurtsev Tomás Pevný 21 6 0 30 Jun 2018
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization G. Scutari Ying Sun 35 61 0 17 May 2018
Momentum and Stochastic Momentum for Stochastic Gradient, Newton, Proximal Point and Subspace Descent Methods Nicolas Loizou Peter Richtárik 19 200 0 27 Dec 2017
Block-Cyclic Stochastic Coordinate Descent for Deep Neural Networks Kensuke Nakamura Stefano Soatto Byung-Woo Hong BDL ODL 43 6 0 20 Nov 2017
GIANT: Globally Improved Approximate Newton Method for Distributed Optimization Shusen Wang Farbod Roosta-Khorasani Peng Xu Michael W. Mahoney 36 127 0 11 Sep 2017
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications A. Chambolle Matthias Joachim Ehrhardt Peter Richtárik Carola-Bibiane Schönlieb 38 184 0 15 Jun 2017
Distributed Coordinate Descent for Generalized Linear Models with Regularization I. Trofimov A. Genkin 26 7 0 07 Nov 2016
Optimization for Large-Scale Machine Learning with Distributed Features and Observations A. Nathan Diego Klabjan 30 13 0 31 Oct 2016
Asynchronous Stochastic Block Coordinate Descent with Variance Reduction Bin Gu Zhouyuan Huo Heng-Chiao Huang 23 10 0 29 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 63 1,878 0 08 Oct 2016
A Primer on Coordinate Descent Algorithms Hao-Jun Michael Shi Shenyinying Tu Yangyang Xu W. Yin 37 90 0 30 Sep 2016
Level Up Your Strategy: Towards a Descriptive Framework for Meaningful Enterprise Gamification Xinghao Pan 29 62 0 29 May 2016
$$\ell_1$ Adaptive Trend Filter via Fast Coordinate Descent$ $\ell_1$ Adaptive Trend Filter via Fast Coordinate Descent Mario Souto J. Garcia G. Amaral 24 5 0 11 Mar 2016
Coordinate Friendly Structures, Algorithms and Applications Zhimin Peng Tianyu Wu Yangyang Xu Ming Yan W. Yin 19 74 0 05 Jan 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 44 172 0 30 Dec 2015
Adaptive Stochastic Primal-Dual Coordinate Descent for Separable Saddle Point Problems Zhanxing Zhu Amos J. Storkey ODL 27 19 0 12 Jun 2015
ARock: an Algorithmic Framework for Asynchronous Parallel Coordinate Updates Zhimin Peng Yangyang Xu Ming Yan W. Yin 19 257 0 08 Jun 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 30 273 0 16 Apr 2015
Convex Optimization for Parallel Energy Minimization K. S. S. Kumar Á. Jiménez Stefanie Jegelka S. Sra Francis R. Bach 31 9 0 05 Mar 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 61 97 0 27 Feb 2015
Adding vs. Averaging in Distributed Primal-Dual Optimization Chenxin Ma Virginia Smith Martin Jaggi Michael I. Jordan Peter Richtárik Martin Takáč FedML 29 176 0 12 Feb 2015
Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation Zheng Qu Peter Richtárik 41 83 0 27 Dec 2014
Accelerated Parallel Optimization Methods for Large Scale Machine Learning Haipeng Luo P. Haffner Jean-François Paiement 21 7 0 25 Nov 2014
Distributed Coordinate Descent for L1-regularized Logistic Regression I. Trofimov A. Genkin 18 15 0 24 Nov 2014
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 38 58 0 21 Nov 2014
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 43 261 0 10 Sep 2014
Large-scale randomized-coordinate descent methods with non-separable linear constraints Sashank J. Reddi Ahmed S. Hefny Carlton Downey Kumar Avinava Dubey S. Sra 23 19 0 09 Sep 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 35 353 0 04 Sep 2014
Matrix Completion under Interval Uncertainty Jakub Mareˇcek Peter Richtárik Martin Takáč 48 19 0 11 Aug 2014
Semi-Stochastic Gradient Descent Methods Jakub Konecný Peter Richtárik ODL 62 237 0 05 Dec 2013
Flexible Parallel Algorithms for Big Data Optimization F. Facchinei Simone Sagratella G. Scutari 43 30 0 11 Nov 2013
Distributed Coordinate Descent Method for Learning with Big Data Peter Richtárik Martin Takáč 50 253 0 08 Oct 2013
Parallel coordinate descent for the Adaboost problem Olivier Fercoq ODL 42 11 0 07 Oct 2013
On the Complexity Analysis of Randomized Block-Coordinate Descent Methods Zhaosong Lu Lin Xiao 33 254 0 21 May 2013