collaborators

5 papers

cs.LG2024

Transcendence: Generative Models Can Outperform The Experts That Train Them

Edwin Zhang, Vincent Zhu, Naomi Saphra +5

Generative models are trained with the simple objective of imitating the conditional probability distribution induced by the data they are trained on. Therefore, when trained on da…

cs.MA2024

A Decision-Language Model (DLM) for Dynamic Restless Multi-Armed Bandit Tasks in Public Health

Nikhil Behari, Edwin Zhang, Yunfan Zhao +3

Restless multi-armed bandits (RMAB) have demonstrated success in optimizing resource allocation for large beneficiary populations in public health settings. Unfortunately, RMAB mod…

cs.AI2024

Social Environment Design

Edwin Zhang, Sadie Zhao, Tonghan Wang +6

Artificial Intelligence (AI) holds promise as a technology that can be used to improve government and economic policy-making. This paper proposes a new research agenda towards this…

cs.LG2023

Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping

Lauren H. Cooke, Harvey Klyne, Edwin Zhang +3

Inverse reinforcement learning (IRL) is computationally challenging, with common approaches requiring the solution of multiple reinforcement learning (RL) sub-problems. This work m…

cs.LG2023

Towards a Pretrained Model for Restless Bandits via Multi-arm Generalization

Yunfan Zhao, Nikhil Behari, Edward Hughes +5

Restless multi-arm bandits (RMABs), a class of resource allocation problems with broad application in areas such as healthcare, online advertising, and anti-poaching, have recently…