Bregman gradient policy optimization
WebJun 23, 2024 · Specifically, we propose a Bregman gradient policy optimization (BGPO) algorithm based on the basic momentum technique and mirror descent iteration. … Webefficient Bregman gradient policy optimization framework based on Bregman divergences and mo-mentum techniques. In particular, we provide a convergence …
Bregman gradient policy optimization
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WebApr 30, 2024 · Abstract. A typical assumption for the convergence of first order optimization methods is the Lipschitz continuity of the gradient of the objective function. However, for … WebJan 27, 2024 · Bregman Gradient Policy Optimization. Feihu Huang, Shangqian Gao, Heng Huang; Computer Science. ICLR. 2024; TLDR. It is proved that BGPO achieves the sample complexity of Õ( −4) for finding -stationary point only requiring one trajectory at each iteration, and VR-BGPO reaches the best known sample complexity for finding an - …
WebFigure 1: Effects of two Bregman Divergences: lp-norm and diagonal term (Diag). - "Bregman Gradient Policy Optimization" WebMany interesting problems can be formulated as convex optimization problems of the form = where :, =, …, are possibly non-differentiable convex functions.The lack of differentiability rules out conventional smooth optimization techniques like the steepest descent method and the conjugate gradient method, but proximal gradient methods can …
WebBregman Gradient Policy Optimization. Authors: Feihu Huang*, Shangqian Gao* and Huang Heng (* indicates equal contribuation) PyTorch Implementation of Bregman … http://arxiv-export3.library.cornell.edu/abs/2106.12112v3
WebSpecifically, we propose a Bregman gradient policy optimization (BGPO) algorithm based on the basic momentum technique and mirror descent iteration. Meanwhile, we further …
WebAug 9, 2024 · DOI: 10.1007/s10589-021-00273-8 Corpus ID: 52585212; Accelerated Bregman proximal gradient methods for relatively smooth convex optimization … majorca all inclusive holidays tuiWebSpecifically, we propose a Bregman gradient policy optimization (BGPO) algorithm based on the basic momentum technique and mirror descent iteration. Meanwhile, we further … majorca all inclusive drinksWebIn this paper, we design a novel Bregman gradient policy optimization framework for reinforcement learning based on Bregman divergences and momentum techniques. Specifically, we propose a Bregman ... majorca adults only hotelWebJun 23, 2024 · 4 Bregman Gradient Policy Optimization. In the section, we propose a novel Bregman gradient policy optimization framework based on Bregman divergences and momentum techniques. We first let f (θ)=−J (θ), the goal of policy-based RL is to solve the following problem: maxθ∈ΘJ (θ) minθ∈Θf (θ). So we have ∇f (θ)=−∇J (θ). majorca beach clubsWebBacktracking line-search is an old yet powerful strategy for finding better step sizes to be used in proximal gradient algorithms. The main principle is to locally find a simple … majorca building melbourneWebBregman Gradient Policy Optimization. The Tenth International Conference on Learning Representations (ICLR 2024), in press. An Xu, Wenqi Li, Pengfei Guo, Dong Yang, Holger Roth, Ali Hatamizadeh, Can Zhao, Daguang Xu, Heng Huang, Ziyue Xu. Closing the Generalization Gap of Cross-silo Federated Medical Image Segmentation. majorca aparthotelWebWe propose a learning framework based on stochastic Bregman iterations, also known as mirror descent, to train sparse neural networks with an inverse scale space approach. We derive a baseline algorithm called LinBreg, an accelerated version using ... majorca and train to soller