610 citations · 2k across the 74 of their papers we have counts for
6 papers · 1 filter
Faster Fixed-Point Methods for Multichain MDPs
Matthew Zurek, Yudong Chen
We study value-iteration (VI) algorithms for solving general (a.k.a. multichain) Markov decision processes (MDPs) under the average-reward criterion, a fundamental but theoreticall…
Optimal Single-Policy Sample Complexity and Transient Coverage for Average-Reward Offline RL
Matthew Zurek, Guy Zamir, Yudong Chen
We study offline reinforcement learning in average-reward MDPs, which presents increased challenges from the perspectives of distribution shift and non-uniform coverage, and has be…
A Piecewise Lyapunov Analysis of Sub-quadratic SGD: Applications to Robust and Quantile Regression
Yixuan Zhang, Dongyan Huo, Yudong Chen +1
Motivated by robust and quantile regression problems, we investigate the stochastic gradient descent (SGD) algorithm for minimizing an objective function that is locally strong…
Optimally Installing Strict Equilibria
Jeremy McMahan, Young Wu, Yudong Chen +2
In this work, we develop a reward design framework for installing a desired behavior as a strict equilibrium across standard solution concepts: dominant strategy equilibrium, Nash…
Span-Agnostic Optimal Sample Complexity and Oracle Inequalities for Average-Reward RL
Matthew Zurek, Yudong Chen
We study the sample complexity of finding an -optimal policy in average-reward Markov Decision Processes (MDPs) with a generative model. The minimax optimal span-based…
The Curve: The Shape of Generalization through the Lens of Norm-based Capacity Control
Yichen Wang, Yudong Chen, Lorenzo Rosasco +1
Understanding how the test risk scales with model complexity is a central question in machine learning. Classical theory is challenged by the learning curves observed for large ove…