610 citations · 2k across the 74 of their papers we have counts for
14 papers · 1 filter
Inference on Dynamic Spatial Autoregressive Models with Change Point Detection
Zetai Cen, Yudong Chen, Clifford Lam
We analyze a varying-coefficient dynamic spatial autoregressive model with spatial fixed effects. One salient feature of the model is the incorporation of multiple spatial weight m…
The Limits of Transfer Reinforcement Learning with Latent Low-rank Structure
Tyler Sam, Yudong Chen, Christina Lee Yu
Many reinforcement learning (RL) algorithms are too costly to use in practice due to the large sizes of the problem's state and action space. To resolve this issue, we study…
Two-Timescale Linear Stochastic Approximation: Constant Stepsizes Go a Long Way
Jeongyeol Kwon, Luke Dotson, Yudong Chen +1
Previous studies on two-timescale stochastic approximation (SA) mainly focused on bounding mean-squared errors under diminishing stepsize schemes. In this work, we investigate {\it…
The Plug-in Approach for Average-Reward and Discounted MDPs: Optimal Sample Complexity Analysis
Matthew Zurek, Yudong Chen
We study the sample complexity of the plug-in approach for learning -optimal policies in average-reward Markov decision processes (MDPs) with a generative model. The p…
Stable Offline Value Function Learning with Bisimulation-based Representations
Brahma S. Pavse, Yudong Chen, Qiaomin Xie +1
In reinforcement learning, offline value function learning is the procedure of using an offline dataset to estimate the expected discounted return from each state when taking actio…
Entry-Specific Matrix Estimation under Arbitrary Sampling Patterns through the Lens of Network Flows
Yudong Chen, Xumei Xi, Christina Lee Yu
Matrix completion tackles the task of predicting missing values in a low-rank matrix based on a sparse set of observed entries. It is often assumed that the observation pattern is…