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Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization

2 January 2023

Papers citing "Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization"

25 / 25 papers shown

Title
Fast Incremental Expectation Maximization for finite-sum optimization: nonasymptotic convergence G. Fort Pierre Gach Eric Moulines 42 9 0 29 Dec 2020
A Stochastic Path-Integrated Differential EstimatoR Expectation Maximization Algorithm G. Fort Eric Moulines Hoi-To Wai TPM 54 7 0 30 Nov 2020
Geom-SPIDER-EM: Faster Variance Reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization G. Fort Eric Moulines Hoi-To Wai TPM 17 6 0 24 Nov 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 78 129 0 25 Aug 2020
Adaptivity of Stochastic Gradient Methods for Nonconvex Optimization Samuel Horváth Lihua Lei Peter Richtárik Michael I. Jordan 104 30 0 13 Feb 2020
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 66 27 0 28 Oct 2019
Variable Metric Proximal Gradient Method with Diagonal Barzilai-Borwein Stepsize Youngsuk Park Sauptik Dhar Stephen P. Boyd Mohak Shah 33 26 0 15 Oct 2019
A Stochastic Composite Gradient Method with Incremental Variance Reduction Junyu Zhang Lin Xiao 51 68 0 24 Jun 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 44 141 0 15 Feb 2019
On the Convergence of A Class of Adam-Type Algorithms for Non-Convex Optimization Xiangyi Chen Sijia Liu Ruoyu Sun Mingyi Hong 58 323 0 08 Aug 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 92 579 0 04 Jul 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 68 147 0 20 Jun 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 65 116 0 13 Feb 2018
Natasha 2: Faster Non-Convex Optimization Than SGD Zeyuan Allen-Zhu ODL 79 246 0 29 Aug 2017
SARAH: A Novel Method for Machine Learning Problems Using Stochastic Recursive Gradient Lam M. Nguyen Jie Liu K. Scheinberg Martin Takáč ODL 167 606 0 01 Mar 2017
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark Schmidt 280 1,220 0 16 Aug 2016
Stochastic Variance Reduction for Nonconvex Optimization Sashank J. Reddi Ahmed S. Hefny S. Sra Barnabás Póczós Alex Smola 99 602 0 19 Mar 2016
Variance Reduction for Faster Non-Convex Optimization Zeyuan Allen-Zhu Elad Hazan ODL 118 392 0 17 Mar 2016
A Linearly-Convergent Stochastic L-BFGS Algorithm Philipp Moritz Robert Nishihara Michael I. Jordan ODL 68 235 0 09 Aug 2015
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives Aaron Defazio Francis R. Bach Simon Lacoste-Julien ODL 133 1,826 0 01 Jul 2014
On perturbed proximal gradient algorithms Yves Atchadé G. Fort Eric Moulines 76 99 0 11 Feb 2014
Stochastic First- and Zeroth-order Methods for Nonconvex Stochastic Programming Saeed Ghadimi Guanghui Lan ODL 122 1,555 0 22 Sep 2013
Proximal Newton-type methods for minimizing composite functions Jason D. Lee Yuekai Sun M. Saunders 84 305 0 07 Jun 2012
Convergence of adaptive and interacting Markov chain Monte Carlo algorithms G. Fort Eric Moulines P. Priouret 57 100 0 14 Mar 2012
Online EM Algorithm for Latent Data Models Olivier Cappé Eric Moulines 147 481 0 27 Dec 2007