Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence

27 February 2024

Papers citing "Taming Nonconvex Stochastic Mirror Descent with General Bregman Divergence"

9 / 9 papers shown

Title
From Gradient Clipping to Normalization for Heavy Tailed SGD Florian Hübler Ilyas Fatkhullin Niao He 40 5 0 17 Oct 2024
Understanding Stochastic Natural Gradient Variational Inference Kaiwen Wu Jacob R. Gardner BDL 41 1 0 04 Jun 2024
Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees Anastasia Koloskova Hadrien Hendrikx Sebastian U. Stich 99 48 0 02 May 2023
Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes Emmeran Johnson Ciara Pike-Burke Patrick Rebeschini 26 11 0 22 Feb 2023
Differentially Private Stochastic Optimization: New Results in Convex and Non-Convex Settings Raef Bassily Cristóbal Guzmán Michael Menart 37 54 0 12 Jul 2021
On the Convergence and Sample Efficiency of Variance-Reduced Policy Gradient Method Junyu Zhang Chengzhuo Ni Zheng Yu Csaba Szepesvári Mengdi Wang 44 66 0 17 Feb 2021
Policy Mirror Descent for Reinforcement Learning: Linear Convergence, New Sampling Complexity, and Generalized Problem Classes Guanghui Lan 87 135 0 30 Jan 2021
Independent Policy Gradient Methods for Competitive Reinforcement Learning C. Daskalakis Dylan J. Foster Noah Golowich 57 158 0 11 Jan 2021
Linear Convergence of Gradient and Proximal-Gradient Methods Under the Polyak-Łojasiewicz Condition Hamed Karimi J. Nutini Mark W. Schmidt 119 1,190 0 16 Aug 2016