Mini-Batch Primal and Dual Methods for SVMs

10 March 2013

Papers citing "Mini-Batch Primal and Dual Methods for SVMs"

33 / 33 papers shown

Title
Revisiting LocalSGD and SCAFFOLD: Improved Rates and Missing Analysis Ruichen Luo Sebastian U Stich Samuel Horváth Martin Takáč 38 0 0 08 Jan 2025
Continuous Concepts Removal in Text-to-image Diffusion Models Tingxu Han Dongrui Liu Yanrong Hu Chunrong Fang Yonglong Zhang Shiqing Ma Tao Zheng Zhenyu Chen Zhenting Wang DiffM 112 2 0 30 Nov 2024
Remove that Square Root: A New Efficient Scale-Invariant Version of AdaGrad Sayantan Choudhury N. Tupitsa Nicolas Loizou Samuel Horváth Martin Takáč Eduard A. Gorbunov 30 1 0 05 Mar 2024
Random-reshuffled SARAH does not need a full gradient computations Aleksandr Beznosikov Martin Takáč 23 7 0 26 Nov 2021
Distributed Second Order Methods with Fast Rates and Compressed Communication Rustem Islamov Xun Qian Peter Richtárik 32 51 0 14 Feb 2021
The Non-IID Data Quagmire of Decentralized Machine Learning Kevin Hsieh Amar Phanishayee O. Mutlu Phillip B. Gibbons 6 556 0 01 Oct 2019
Quasi-Newton Methods for Machine Learning: Forget the Past, Just Sample A. Berahas Majid Jahani Peter Richtárik Martin Takávc 16 40 0 28 Jan 2019
Don't Use Large Mini-Batches, Use Local SGD Tao R. Lin Sebastian U. Stich Kumar Kshitij Patel Martin Jaggi 54 429 0 22 Aug 2018
The Effect of Network Width on the Performance of Large-batch Training Lingjiao Chen Hongyi Wang Jinman Zhao Dimitris Papailiopoulos Paraschos Koutris 13 22 0 11 Jun 2018
Stochastic Primal-Dual Hybrid Gradient Algorithm with Arbitrary Sampling and Imaging Applications A. Chambolle Matthias Joachim Ehrhardt Peter Richtárik Carola-Bibiane Schönlieb 29 184 0 15 Jun 2017
Federated Multi-Task Learning Virginia Smith Chao-Kai Chiang Maziar Sanjabi Ameet Talwalkar FedML 15 1,776 0 30 May 2017
Diving into the shallows: a computational perspective on large-scale shallow learning Siyuan Ma M. Belkin 24 75 0 30 Mar 2017
Distributed Dual Coordinate Ascent in General Tree Networks and Communication Network Effect on Synchronous Machine Learning Myung Cho Lifeng Lai Weiyu Xu 12 1 0 14 Mar 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč ODL 28 596 0 01 Mar 2017
Optimization for Large-Scale Machine Learning with Distributed Features and Observations A. Nathan Diego Klabjan 27 13 0 31 Oct 2016
Parallelizing Stochastic Gradient Descent for Least Squares Regression: mini-batching, averaging, and model misspecification Prateek Jain Sham Kakade Rahul Kidambi Praneeth Netrapalli Aaron Sidford MoMe 15 36 0 12 Oct 2016
Federated Optimization: Distributed Machine Learning for On-Device Intelligence Jakub Konecný H. B. McMahan Daniel Ramage Peter Richtárik FedML 27 1,876 0 08 Oct 2016
A General Distributed Dual Coordinate Optimization Framework for Regularized Loss Minimization Shun Zheng Jialei Wang Fen Xia Wenyuan Xu Tong Zhang 13 22 0 13 Apr 2016
Training Region-based Object Detectors with Online Hard Example Mining Abhinav Shrivastava Abhinav Gupta Ross B. Girshick ObjD 49 2,399 0 12 Apr 2016
Optimal Margin Distribution Machine Teng Zhang Zhi-Hua Zhou 20 72 0 12 Apr 2016
Even Faster Accelerated Coordinate Descent Using Non-Uniform Sampling Zeyuan Allen-Zhu Zheng Qu Peter Richtárik Yang Yuan 38 172 0 30 Dec 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 22 273 0 16 Apr 2015
Stochastic Dual Coordinate Ascent with Adaptive Probabilities Dominik Csiba Zheng Qu Peter Richtárik ODL 53 97 0 27 Feb 2015
Coordinate Descent with Arbitrary Sampling II: Expected Separable Overapproximation Zheng Qu Peter Richtárik 33 83 0 27 Dec 2014
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 32 58 0 21 Nov 2014
Stochastic Primal-Dual Coordinate Method for Regularized Empirical Risk Minimization Yuchen Zhang Xiao Lin 40 261 0 10 Sep 2014
Communication-Efficient Distributed Dual Coordinate Ascent Martin Jaggi Virginia Smith Martin Takáč Jonathan Terhorst S. Krishnan Thomas Hofmann Michael I. Jordan 26 353 0 04 Sep 2014
Semi-Stochastic Gradient Descent Methods Jakub Konecný Peter Richtárik ODL 58 237 0 05 Dec 2013
Stochastic Dual Coordinate Ascent with Alternating Direction Multiplier Method Taiji Suzuki 32 8 0 04 Nov 2013
Distributed Coordinate Descent Method for Learning with Big Data Peter Richtárik Martin Takáč 36 253 0 08 Oct 2013
Parallel coordinate descent for the Adaboost problem Olivier Fercoq ODL 34 11 0 07 Oct 2013
Accelerated Proximal Stochastic Dual Coordinate Ascent for Regularized Loss Minimization Shai Shalev-Shwartz Tong Zhang ODL 49 462 0 10 Sep 2013
Optimal Distributed Online Prediction using Mini-Batches O. Dekel Ran Gilad-Bachrach Ohad Shamir Lin Xiao 177 683 0 07 Dec 2010