Variance Reduction for Faster Non-Convex Optimization

17 March 2016

Papers citing "Variance Reduction for Faster Non-Convex Optimization"

50 / 78 papers shown

Title
SAPPHIRE: Preconditioned Stochastic Variance Reduction for Faster Large-Scale Statistical Learning Jingruo Sun Zachary Frangella Madeleine Udell 36 0 0 28 Jan 2025
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction Xinwei Zhang Zhiqi Bu Borja Balle Mingyi Hong Meisam Razaviyayn Vahab Mirrokni 78 2 0 04 Oct 2024
Debiasing Federated Learning with Correlated Client Participation Zhenyu Sun Ziyang Zhang Zheng Xu Gauri Joshi Pranay Sharma Ermin Wei FedML 29 0 0 02 Oct 2024
SOREL: A Stochastic Algorithm for Spectral Risks Minimization Yuze Ge Rujun Jiang 38 0 0 19 Jul 2024
Stochastic Halpern iteration in normed spaces and applications to reinforcement learning Mario Bravo Juan Pablo Contreras 48 3 0 19 Mar 2024
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems Yanjie Zhong Jiaqi Li Soumendra Lahiri 27 1 0 29 Jan 2024
A Coefficient Makes SVRG Effective Yida Yin Zhiqiu Xu Zhiyuan Li Trevor Darrell Zhuang Liu 33 1 0 09 Nov 2023
Convergence of Sign-based Random Reshuffling Algorithms for Nonconvex Optimization Zhen Qin Zhishuai Liu Pan Xu 26 1 0 24 Oct 2023
Sarah Frank-Wolfe: Methods for Constrained Optimization with Best Rates and Practical Features Aleksandr Beznosikov David Dobre Gauthier Gidel 25 5 0 23 Apr 2023
Balance is Essence: Accelerating Sparse Training via Adaptive Gradient Correction Bowen Lei Dongkuan Xu Ruqi Zhang Shuren He Bani Mallick 37 6 0 09 Jan 2023
Stochastic Variable Metric Proximal Gradient with variance reduction for non-convex composite optimization G. Fort Eric Moulines 46 6 0 02 Jan 2023
Variance-Reduced Conservative Policy Iteration Naman Agarwal Brian Bullins Karan Singh 32 3 0 12 Dec 2022
Zeroth-Order Alternating Gradient Descent Ascent Algorithms for a Class of Nonconvex-Nonconcave Minimax Problems Zi Xu Ziqi Wang Junlin Wang Y. Dai 21 11 0 24 Nov 2022
An Improved Analysis of (Variance-Reduced) Policy Gradient and Natural Policy Gradient Methods Yanli Liu Kaipeng Zhang Tamer Basar W. Yin 48 102 0 15 Nov 2022
Adaptive Stochastic Variance Reduction for Non-convex Finite-Sum Minimization Ali Kavis Stratis Skoulakis Kimon Antonakopoulos L. Dadi V. Cevher 24 15 0 03 Nov 2022
Do We Need to Penalize Variance of Losses for Learning with Label Noise? Yexiong Lin Yu Yao Yuxuan Du Jun Yu Bo Han Biwei Huang Tongliang Liu NoLa 53 3 0 30 Jan 2022
Distributed Policy Gradient with Variance Reduction in Multi-Agent Reinforcement Learning Xiaoxiao Zhao Jinlong Lei Li Li Jie-bin Chen OffRL 18 2 0 25 Nov 2021
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen Dongruo Zhou Quanquan Gu 43 1 0 25 Oct 2021
On Improving Model-Free Algorithms for Decentralized Multi-Agent Reinforcement Learning Weichao Mao Lin F. Yang Kaipeng Zhang Tamer Bacsar 39 57 0 12 Oct 2021
Stochastic Anderson Mixing for Nonconvex Stochastic Optimization Fu Wei Chenglong Bao Yang Liu 30 19 0 04 Oct 2021
Improved Learning Rates for Stochastic Optimization: Two Theoretical Viewpoints Shaojie Li Yong Liu 26 13 0 19 Jul 2021
Proxy Convexity: A Unified Framework for the Analysis of Neural Networks Trained by Gradient Descent Spencer Frei Quanquan Gu 26 25 0 25 Jun 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 43 14 0 21 Mar 2021
IntSGD: Adaptive Floatless Compression of Stochastic Gradients Konstantin Mishchenko Bokun Wang D. Kovalev Peter Richtárik 75 15 0 16 Feb 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 15 7 0 12 Feb 2021
Efficient Semi-Implicit Variational Inference Vincent Moens Hang Ren A. Maraval Rasul Tutunov Jun Wang H. Ammar 85 6 0 15 Jan 2021
Optimization for Supervised Machine Learning: Randomized Algorithms for Data and Parameters Filip Hanzely 34 0 0 26 Aug 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 31 126 0 25 Aug 2020
A Stochastic Subgradient Method for Distributionally Robust Non-Convex Learning Mert Gurbuzbalaban A. Ruszczynski Landi Zhu 26 9 0 08 Jun 2020
Momentum-based variance-reduced proximal stochastic gradient method for composite nonconvex stochastic optimization Yangyang Xu Yibo Xu 17 23 0 31 May 2020
A Data-Driven Frequency Scaling Approach for Deadline-aware Energy Efficient Scheduling on Graphics Processing Units (GPUs) Shashikant Ilager R. Muralidhar K. Ramamohanarao Rajkumar Buyya 11 13 0 17 Apr 2020
Variance Reduced Coordinate Descent with Acceleration: New Method With a Surprising Application to Finite-Sum Problems Filip Hanzely D. Kovalev Peter Richtárik 35 17 0 11 Feb 2020
On the Global Convergence of (Fast) Incremental Expectation Maximization Methods Belhal Karimi Hoi-To Wai Eric Moulines M. Lavielle 32 27 0 28 Oct 2019
History-Gradient Aided Batch Size Adaptation for Variance Reduced Algorithms Kaiyi Ji Zhe Wang Bowen Weng Yi Zhou Wei Zhang Yingbin Liang ODL 18 5 0 21 Oct 2019
Sample Efficient Policy Gradient Methods with Recursive Variance Reduction Pan Xu F. Gao Quanquan Gu 31 83 0 18 Sep 2019
Stochastic First-order Methods for Convex and Nonconvex Functional Constrained Optimization Digvijay Boob Qi Deng Guanghui Lan 52 92 0 07 Aug 2019
Distributed Inexact Successive Convex Approximation ADMM: Analysis-Part I Sandeep Kumar K. Rajawat Daniel P. Palomar 19 4 0 21 Jul 2019
Stabilized SVRG: Simple Variance Reduction for Nonconvex Optimization Rong Ge Zhize Li Weiyao Wang Xiang Wang 19 33 0 01 May 2019
Reducing Noise in GAN Training with Variance Reduced Extragradient Tatjana Chavdarova Gauthier Gidel F. Fleuret Simon Lacoste-Julien 25 134 0 18 Apr 2019
On the Ineffectiveness of Variance Reduced Optimization for Deep Learning Aaron Defazio Léon Bottou UQCV DRL 23 112 0 11 Dec 2018
Stagewise Training Accelerates Convergence of Testing Error Over SGD Zhuoning Yuan Yan Yan Rong Jin Tianbao Yang 60 11 0 10 Dec 2018
Stochastic Optimization for DC Functions and Non-smooth Non-convex Regularizers with Non-asymptotic Convergence Yi Tian Xu Qi Qi Qihang Lin Rong Jin Tianbao Yang 37 41 0 28 Nov 2018
A Local Regret in Nonconvex Online Learning Sergul Aydore Lee H. Dicker Dean Phillips Foster 28 3 0 13 Nov 2018
SpiderBoost and Momentum: Faster Stochastic Variance Reduction Algorithms Zhe Wang Kaiyi Ji Yi Zhou Yingbin Liang Vahid Tarokh ODL 35 81 0 25 Oct 2018
Continuous-time Models for Stochastic Optimization Algorithms Antonio Orvieto Aurelien Lucchi 19 31 0 05 Oct 2018
Weakly-Convex Concave Min-Max Optimization: Provable Algorithms and Applications in Machine Learning Hassan Rafique Mingrui Liu Qihang Lin Tianbao Yang 15 107 0 04 Oct 2018
SPIDER: Near-Optimal Non-Convex Optimization via Stochastic Path Integrated Differential Estimator Cong Fang C. J. Li Zhouchen Lin Tong Zhang 50 570 0 04 Jul 2018
A Simple Stochastic Variance Reduced Algorithm with Fast Convergence Rates Kaiwen Zhou Fanhua Shang James Cheng 14 74 0 28 Jun 2018
Stochastic Nested Variance Reduction for Nonconvex Optimization Dongruo Zhou Pan Xu Quanquan Gu 25 146 0 20 Jun 2018
Stochastic Variance-Reduced Policy Gradient Matteo Papini Damiano Binaghi Giuseppe Canonaco Matteo Pirotta Marcello Restelli 19 174 0 14 Jun 2018