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SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points

19 April 2019

Papers citing "SSRGD: Simple Stochastic Recursive Gradient Descent for Escaping Saddle Points"

28 / 28 papers shown

Title
Hessian-guided Perturbed Wasserstein Gradient Flows for Escaping Saddle Points Naoya Yamamoto Juno Kim Taiji Suzuki 12 0 0 21 Sep 2025
Second-Order Convergence in Private Stochastic Non-Convex Optimization Youming Tao Zuyuan Zhang Dongxiao Yu Xiuzhen Cheng Falko Dressler Di Wang 98 2 0 21 May 2025
Stochastic First-Order Methods with Non-smooth and Non-Euclidean Proximal Terms for Nonconvex High-Dimensional Stochastic Optimization Yue Xie Jiawen Bi Hongcheng Liu 94 0 0 27 Jun 2024
Probabilistic Guarantees of Stochastic Recursive Gradient in Non-Convex Finite Sum Problems Yanjie Zhong Jiaqi Li Soumendra Lahiri 83 1 0 29 Jan 2024
Escaping Saddle Points in Heterogeneous Federated Learning via Distributed SGD with Communication Compression Sijin Chen Zhize Li Yuejie Chi FedML 117 5 0 29 Oct 2023
Faster Gradient-Free Algorithms for Nonsmooth Nonconvex Stochastic Optimization Le‐Yu Chen Jing Xu Luo Luo 130 21 0 16 Jan 2023
Versatile Single-Loop Method for Gradient Estimator: First and Second Order Optimality, and its Application to Federated Learning Kazusato Oko Shunta Akiyama Tomoya Murata Taiji Suzuki FedML 120 0 0 01 Sep 2022
Simple and Optimal Stochastic Gradient Methods for Nonsmooth Nonconvex Optimization Zhize Li Jian Li 147 8 0 22 Aug 2022
Anchor Sampling for Federated Learning with Partial Client Participation Feijie Wu Song Guo Zhihao Qu Shiqi He Ziming Liu Jing Gao FedML 129 20 0 13 Jun 2022
Improved Convergence Rate of Stochastic Gradient Langevin Dynamics with Variance Reduction and its Application to Optimization Yuri Kinoshita Taiji Suzuki 142 18 0 30 Mar 2022
Tackling benign nonconvexity with smoothing and stochastic gradients Harsh Vardhan Sebastian U. Stich 125 8 0 18 Feb 2022
Escaping Saddle Points with Bias-Variance Reduced Local Perturbed SGD for Communication Efficient Nonconvex Distributed Learning Tomoya Murata Taiji Suzuki FedML 107 3 0 12 Feb 2022
Faster Rates for Compressed Federated Learning with Client-Variance Reduction Haoyu Zhao Konstantin Burlachenko Zhize Li Peter Richtárik FedML 172 16 0 24 Dec 2021
Escape saddle points by a simple gradient-descent based algorithm Chenyi Zhang Tongyang Li ODL 92 15 0 28 Nov 2021
Faster Perturbed Stochastic Gradient Methods for Finding Local Minima Zixiang Chen Dongruo Zhou Quanquan Gu 111 2 0 25 Oct 2021
DESTRESS: Computation-Optimal and Communication-Efficient Decentralized Nonconvex Finite-Sum Optimization Boyue Li Zhize Li Yuejie Chi 132 23 0 04 Oct 2021
FedPAGE: A Fast Local Stochastic Gradient Method for Communication-Efficient Federated Learning Haoyu Zhao Zhize Li Peter Richtárik FedML 107 31 0 10 Aug 2021
CANITA: Faster Rates for Distributed Convex Optimization with Communication Compression Zhize Li Peter Richtárik 116 32 0 20 Jul 2021
ANITA: An Optimal Loopless Accelerated Variance-Reduced Gradient Method Zhize Li 173 16 0 21 Mar 2021
ZeroSARAH: Efficient Nonconvex Finite-Sum Optimization with Zero Full Gradient Computation Zhize Li Slavomír Hanzely Peter Richtárik 99 33 0 02 Mar 2021
Stochastic Gradient Langevin Dynamics with Variance Reduction Zhishen Huang Stephen Becker 104 9 0 12 Feb 2021
Bias-Variance Reduced Local SGD for Less Heterogeneous Federated Learning Tomoya Murata Taiji Suzuki FedML 133 53 0 05 Feb 2021
Escape saddle points faster on manifolds via perturbed Riemannian stochastic recursive gradient Andi Han Junbin Gao 97 5 0 23 Oct 2020
PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization Zhize Li Hongyan Bao Xiangliang Zhang Peter Richtárik ODL 196 139 0 25 Aug 2020
A Unified Analysis of Stochastic Gradient Methods for Nonconvex Federated Optimization Zhize Li Peter Richtárik FedML 133 40 0 12 Jun 2020
A Hybrid Stochastic Optimization Framework for Stochastic Composite Nonconvex Optimization Quoc Tran-Dinh Nhan H. Pham T. Dzung Lam M. Nguyen 117 55 0 08 Jul 2019
A Fast Anderson-Chebyshev Acceleration for Nonlinear Optimization Zhize Li Jian Li 105 20 0 07 Sep 2018
Stochastic Gradient Hamiltonian Monte Carlo with Variance Reduction for Bayesian Inference Zhize Li Tianyi Zhang Shuyu Cheng Jun Yu Li Jian Li BDL 95 19 0 29 Mar 2018