Turnitin
降AI改写
早检测系统
早降重系统
Turnitin-UK版
万方检测-期刊版
维普编辑部版
Grammarly检测
Paperpass检测
checkpass检测
PaperYY检测
Almost sure convergence rates of stochastic gradient methods under gradient domination
Stochastic gradient methods are among the most important algorithms in training machine
learning problems. While classical assumptions such as strong convexity allow a simple …
learning problems. While classical assumptions such as strong convexity allow a simple …
Practical principled policy optimization for finite MDPs
We consider (stochastic) softmax policy gradient (PG) methods for finite Markov Decision
Processes (MDP). While the PG objective is not concave, recent research has used …
Processes (MDP). While the PG objective is not concave, recent research has used …
Dynamic approaches for stochastic gradient methods in reinforcement learning
S Klein - 2024 - madoc.bib.uni-mannheim.de
This work addresses the convergence behaviour of first-order optimization methods in the
context of reinforcement learning. Specifically, we analyse the vanilla Policy Gradient (PG) …
context of reinforcement learning. Specifically, we analyse the vanilla Policy Gradient (PG) …