mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting

17 October 2014

Papers citing "mS2GD: Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting"

11 / 11 papers shown

Title
AdaBest: Minimizing Client Drift in Federated Learning via Adaptive Bias Estimation Farshid Varno Marzie Saghayi Laya Rafiee Sharut Gupta Stan Matwin Mohammad Havaei FedML 146 31 0 27 Apr 2022
Stochastic, Distributed and Federated Optimization for Machine Learning Jakub Konecný FedML 83 38 0 04 Jul 2017
Projected Semi-Stochastic Gradient Descent Method with Mini-Batch Scheme under Weak Strong Convexity Assumption Jie Liu Martin Takáč ODL 117 4 0 16 Dec 2016
Importance Sampling for Minibatches Dominik Csiba Peter Richtárik 111 117 0 06 Feb 2016
Kalman-based Stochastic Gradient Method with Stop Condition and Insensitivity to Conditioning V. Patel 94 35 0 03 Dec 2015
Distributed Mini-Batch SDCA Martin Takáč Peter Richtárik Nathan Srebro 87 50 0 29 Jul 2015
Primal Method for ERM with Flexible Mini-batching Schemes and Non-convex Losses Dominik Csiba Peter Richtárik 92 23 0 07 Jun 2015
Mini-Batch Semi-Stochastic Gradient Descent in the Proximal Setting Jakub Konecný Jie Liu Peter Richtárik Martin Takáč ODL 146 273 0 16 Apr 2015
SDNA: Stochastic Dual Newton Ascent for Empirical Risk Minimization Zheng Qu Peter Richtárik Martin Takáč Olivier Fercoq ODL 131 99 0 08 Feb 2015
Coordinate Descent with Arbitrary Sampling I: Algorithms and Complexity Zheng Qu Peter Richtárik 83 130 0 27 Dec 2014
Randomized Dual Coordinate Ascent with Arbitrary Sampling Zheng Qu Peter Richtárik Tong Zhang 155 58 0 21 Nov 2014