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Minimizing Finite Sums with the Stochastic Average Gradient

10 September 2013

Mark Schmidt

Nicolas Le Roux

Francis R. Bach

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Papers citing "Minimizing Finite Sums with the Stochastic Average Gradient"

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Title
$Convergence of Gradient Algorithms for Nonconvex C^{1+alpha} Cost Functions$ Convergence of Gradient Algorithms for Nonconvex C^{1+alpha} Cost Functions Zixuan Wang Shanjian Tang 31 0 0 01 Dec 2020
Relative Lipschitzness in Extragradient Methods and a Direct Recipe for Acceleration Michael B. Cohen Aaron Sidford Kevin Tian 77 41 0 12 Nov 2020
Self-Tuning Stochastic Optimization with Curvature-Aware Gradient Filtering Ricky T. Q. Chen Dami Choi Lukas Balles David Duvenaud Philipp Hennig ODL 79 6 0 09 Nov 2020
Gradient-Based Empirical Risk Minimization using Local Polynomial Regression Ali Jadbabaie A. Makur Devavrat Shah 406 6 0 04 Nov 2020
Local SGD: Unified Theory and New Efficient Methods Eduard A. Gorbunov Filip Hanzely Peter Richtárik FedML 93 111 0 03 Nov 2020
Asynchronous Parallel Stochastic Quasi-Newton Methods Qianqian Tong Guannan Liang Xingyu Cai Chunjiang Zhu J. Bi ODL 86 9 0 02 Nov 2020
Tight Lower Complexity Bounds for Strongly Convex Finite-Sum Optimization Min Zhang Yao Shu Kun He 37 1 0 17 Oct 2020
Structured Logconcave Sampling with a Restricted Gaussian Oracle Y. Lee Ruoqi Shen Kevin Tian 79 73 0 07 Oct 2020
Variance-Reduced Methods for Machine Learning Robert Mansel Gower Mark Schmidt Francis R. Bach Peter Richtárik 109 117 0 02 Oct 2020
A variable metric mini-batch proximal stochastic recursive gradient algorithm with diagonal Barzilai-Borwein stepsize Tengteng Yu Xinwei Liu Yuhong Dai Jie Sun 84 4 0 02 Oct 2020
Understanding the Role of Adversarial Regularization in Supervised Learning Litu Rout 44 3 0 01 Oct 2020
Projection-Free Adaptive Gradients for Large-Scale Optimization Cyrille W. Combettes Christoph Spiegel Sebastian Pokutta ODL 92 11 0 29 Sep 2020
Cross Learning in Deep Q-Networks Xing Wang A. Vinel 25 2 0 29 Sep 2020
A general framework for decentralized optimization with first-order methods Ran Xin Shi Pu Angelia Nedić U. Khan 65 89 0 12 Sep 2020
Neural Neighborhood Encoding for Classification Kaushik Sinha Parikshit Ram 67 1 0 19 Aug 2020
Privacy-Preserving Asynchronous Federated Learning Algorithms for Multi-Party Vertically Collaborative Learning Bin Gu An Xu Zhouyuan Huo Cheng Deng Heng-Chiao Huang FedML 99 30 0 14 Aug 2020
A Survey on Large-scale Machine Learning Meng Wang Weijie Fu Xiangnan He Shijie Hao Xindong Wu 84 112 0 10 Aug 2020
On the Regularization Effect of Stochastic Gradient Descent applied to Least Squares Stefan Steinerberger 23 1 0 27 Jul 2020
Langevin Monte Carlo: random coordinate descent and variance reduction Zhiyan Ding Qin Li BDL 52 12 0 26 Jul 2020
Stochastic Hamiltonian Gradient Methods for Smooth Games Nicolas Loizou Hugo Berard Alexia Jolicoeur-Martineau Pascal Vincent Simon Lacoste-Julien Ioannis Mitliagkas 59 50 0 08 Jul 2020
Conditional gradient methods for stochastically constrained convex minimization Maria-Luiza Vladarean Ahmet Alacaoglu Ya-Ping Hsieh Volkan Cevher 49 3 0 07 Jul 2020
Streaming Complexity of SVMs Alexandr Andoni Collin Burns Yi Li S. Mahabadi David P. Woodruff 47 5 0 07 Jul 2020
Stochastic Stein Discrepancies Jackson Gorham Anant Raj Lester W. Mackey 113 38 0 06 Jul 2020
A Multilevel Approach to Training Vanessa Braglia Alena Kopanicáková Rolf Krause 26 2 0 28 Jun 2020
Dual-Free Stochastic Decentralized Optimization with Variance Reduction Hadrien Hendrikx Francis R. Bach Laurent Massoulié 52 26 0 25 Jun 2020
Unified Analysis of Stochastic Gradient Methods for Composite Convex and Smooth Optimization Ahmed Khaled Othmane Sebbouh Nicolas Loizou Robert Mansel Gower Peter Richtárik 119 47 0 20 Jun 2020
SGD for Structured Nonconvex Functions: Learning Rates, Minibatching and Interpolation Robert Mansel Gower Othmane Sebbouh Nicolas Loizou 120 76 0 18 Jun 2020
AdaS: Adaptive Scheduling of Stochastic Gradients Mahdi S. Hosseini Konstantinos N. Plataniotis ODL 77 12 0 11 Jun 2020
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo Zhiyan Ding Qin Li BDL 42 0 0 10 Jun 2020
SONIA: A Symmetric Blockwise Truncated Optimization Algorithm Majid Jahani M. Nazari R. Tappenden A. Berahas Martin Takávc ODL 55 10 0 06 Jun 2020
Improved SVRG for quadratic functions N. Kahalé 40 0 0 01 Jun 2020
CoolMomentum: A Method for Stochastic Optimization by Langevin Dynamics with Simulated Annealing O. Borysenko M. Byshkin ODL 56 14 0 29 May 2020
Boosting First-Order Methods by Shifting Objective: New Schemes with Faster Worst-Case Rates Kaiwen Zhou Anthony Man-Cho So James Cheng 59 5 0 25 May 2020
An Optimal Algorithm for Decentralized Finite Sum Optimization Hadrien Hendrikx Francis R. Bach Laurent Massoulie 66 45 0 20 May 2020
A Riemannian Primal-dual Algorithm Based on Proximal Operator and its Application in Metric Learning Shijun Wang Baocheng Zhu Lintao Ma Yuan Qi 32 0 0 19 May 2020
The Impact of the Mini-batch Size on the Variance of Gradients in Stochastic Gradient Descent Xin-Yao Qian Diego Klabjan ODL 72 36 0 27 Apr 2020
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning Wenhao Li Bo Jin Xiangfeng Wang Junchi Yan H. Zha 100 21 0 17 Apr 2020
Analysis of Stochastic Gradient Descent in Continuous Time J. Latz 81 41 0 15 Apr 2020
Communication-efficient Variance-reduced Stochastic Gradient Descent H. S. Ghadikolaei Sindri Magnússon 54 3 0 10 Mar 2020
Buffered Asynchronous SGD for Byzantine Learning Yi-Rui Yang Wu-Jun Li FedML 38 5 0 02 Mar 2020
Stochastic Frank-Wolfe for Constrained Finite-Sum Minimization Geoffrey Negiar Gideon Dresdner Alicia Y. Tsai L. Ghaoui Francesco Locatello Robert M. Freund Fabian Pedregosa 76 25 0 27 Feb 2020
General Framework for Binary Classification on Top Samples Lukáš Adam V. Mácha Václav Smídl Tomás Pevný 47 5 0 25 Feb 2020
$Can speed up the convergence rate of stochastic gradient methods to $\mathcal{O}(1/k^2)$ by a gradient averaging strategy?$ Can speed up the convergence rate of stochastic gradient methods to $\mathcal{O}(1/k^2)$ by a gradient averaging strategy? Xin Xu Xiaopeng Luo 23 1 0 25 Feb 2020
Statistical Adaptive Stochastic Gradient Methods Pengchuan Zhang Hunter Lang Qiang Liu Lin Xiao ODL 74 11 0 25 Feb 2020
Improving Sampling Accuracy of Stochastic Gradient MCMC Methods via Non-uniform Subsampling of Gradients Ruilin Li Xin Wang H. Zha Molei Tao 34 4 0 20 Feb 2020
Sampling and Update Frequencies in Proximal Variance-Reduced Stochastic Gradient Methods Martin Morin Pontus Giselsson 49 4 0 13 Feb 2020
Gradient tracking and variance reduction for decentralized optimization and machine learning Ran Xin S. Kar U. Khan 49 10 0 13 Feb 2020
On the Complexity of Minimizing Convex Finite Sums Without Using the Indices of the Individual Functions Yossi Arjevani Amit Daniely Stefanie Jegelka Hongzhou Lin 63 2 0 09 Feb 2020
Adaptive Stochastic Optimization Frank E. Curtis K. Scheinberg ODL 48 29 0 18 Jan 2020
Stochastic Recursive Variance Reduction for Efficient Smooth Non-Convex Compositional Optimization Huizhuo Yuan Xiangru Lian Ji Liu 60 13 0 31 Dec 2019