Stochastic Nested Variance Reduction for Nonconvex Optimization

20 June 2018

Quanquan Gu

Papers citing "Stochastic Nested Variance Reduction for Nonconvex Optimization"

27 / 27 papers shown

Title
Extended convexity and smoothness and their applications in deep learning Binchuan Qi Wei Gong Li Li 61 0 0 08 Oct 2024
Cubic regularized subspace Newton for non-convex optimization Jim Zhao Aurélien Lucchi N. Doikov 20 5 0 24 Jun 2024
Random Scaling and Momentum for Non-smooth Non-convex Optimization Qinzi Zhang Ashok Cutkosky 35 4 0 16 May 2024
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning Mario Bravo Juan Pablo Contreras 40 3 0 19 Mar 2024
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 25 1 0 09 Nov 2023
Federated Multi-Sequence Stochastic Approximation with Local Hypergradient Estimation Davoud Ataee Tarzanagh Mingchen Li Pranay Sharma Samet Oymak 24 0 0 02 Jun 2023
Stochastic Dimension-reduced Second-order Methods for Policy Optimization Jinsong Liu Chen Xie Qinwen Deng Dongdong Ge Yi-Li Ye 19 1 0 28 Jan 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 44 6 0 02 Jan 2023
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 23 15 0 28 Nov 2021
Whole Brain Segmentation with Full Volume Neural Network Yeshu Li Jianwei Cui Yilun Sheng Xiao Liang Jingdong Wang E. Chang Yan Xu 27 11 0 29 Oct 2021
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen Dongruo Zhou Quanquan Gu 25 1 0 25 Oct 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent Spencer Frei Quanquan Gu 15 25 0 25 Jun 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 28 14 0 21 Mar 2021
Accelerating Convergence of Replica Exchange Stochastic Gradient MCMC via Variance Reduction Wei Deng Qi Feng G. Karagiannis Guang Lin F. Liang 14 8 0 02 Oct 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 24 125 0 25 Aug 2020
Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations Yossi Arjevani Y. Carmon John C. Duchi Dylan J. Foster Ayush Sekhari Karthik Sridharan 69 53 0 24 Jun 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 27 17 0 11 Feb 2020
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization Digvijay Boob Qi Deng Guanghui Lan 39 92 0 07 Aug 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 17 33 0 01 May 2019
ProxSARAH: An Efficient Algorithmic Framework for Stochastic Composite Nonconvex Optimization Nhan H. Pham Lam M. Nguyen Dzung Phan Quoc Tran-Dinh 11 139 0 15 Feb 2019
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 33 568 0 04 Jul 2018
A Simple Proximal Stochastic Gradient Method for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 33 116 0 13 Feb 2018
Katyusha X: Practical Momentum Method for Stochastic Sum-of-Nonconvex Optimization Zeyuan Allen-Zhu ODL 42 52 0 12 Feb 2018
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 124 1,198 0 16 Aug 2016
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 177 1,185 0 30 Nov 2014
A Proximal Stochastic Gradient Method with Progressive Variance Reduction Lin Xiao Tong Zhang ODL 76 736 0 19 Mar 2014
Incremental Majorization-Minimization Optimization with Application to Large-Scale Machine Learning Julien Mairal 68 317 0 18 Feb 2014