papers
Publications (3)
cs.LG2021
Linear Representation Meta-Reinforcement Learning for Instant Adaptation
Matt Peng, Banghua Zhu, Jiantao Jiao
This paper introduces Fast Linearized Adaptive Policy (FLAP), a new meta-reinforcement learning (meta-RL) method that is able to extrapolate well to out-of-distribution tasks witho…
cs.CY2025
The GPT Surprise: Offering Large Language Model Chat in a Massive Coding Class Reduced Engagement but Increased Adopters Exam Performances
Allen Nie, Yash Chandak, Miroslav Suzara +6
Large language models (LLMs) are quickly being adopted in a wide range of learning experiences, especially via ubiquitous and broadly accessible chat interfaces like ChatGPT and Co…
cs.LG2021
An Adaptive State Aggregation Algorithm for Markov Decision Processes
Guanting Chen, Johann Demetrio Gaebler, Matt Peng +2
Value iteration is a well-known method of solving Markov Decision Processes (MDPs) that is simple to implement and boasts strong theoretical convergence guarantees. However, the co…