Zaiwei Chen

Assistant Professor, Purdue University

3 papers at NeurIPS 2025

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Poster Session 2

1 paper

Wednesday, December 3, 2025 · 4:30 PM → 7:30 PM

Exhibit Hall C,D,E

Maximizing the Value of Predictions in Control: Accuracy Is Not Enough

#3309 · Yiheng Lin, Christopher Yeh, Zaiwei Chen, Adam Wierman

We study the value of stochastic predictions in online optimal control with random disturbances.

Poster Session 3

2 papers

Thursday, December 4, 2025 · 11:00 AM → 2:00 PM

Exhibit Hall C,D,E

Non-Asymptotic Guarantees for Average-Reward Q-Learning with Adaptive Stepsizes

#5416 · Zaiwei Chen

This work presents the first finite-time analysis of average-reward Q-learning with asynchronous updates based on a single trajectory of Markovian samples.

Reinforcement Learning with Imperfect Transition Predictions: A Bellman-Jensen Approach

#5312 Spotlight · Chenbei Lu, Zaiwei Chen, Tongxin Li, Chenye Wu, Adam Wierman

We introduce a Bayesian value framework and a Bellman–Jensen Gap analysis to rigorously quantify and exploit imperfect multi‐step transition predictions, and present BOLA, the first provable sample‐efficient algorithm for RL with predictions.