2 citations · 3 across the 15 of their papers we have counts for
5 papers · 1 filter
Incentives in Federated Learning with Heterogeneous Agents
Ariel D. Procaccia, Han Shao, Itai Shapira
Federated learning promises significant sample-efficiency gains by pooling data across multiple agents, yet incentive misalignment is an obstacle: each update is costly to the cont…
COPO: Consistency-Aware Policy Optimization
Jinghang Han, Jiawei Chen, Hang Shao +7
Reinforcement learning has significantly enhanced the reasoning capabilities of Large Language Models (LLMs) in complex problem-solving tasks. Recently, the introduction of DeepSee…
Should Decision-Makers Reveal Classifiers in Online Strategic Classification?
Han Shao, Shuo Xie, Kunhe Yang
Strategic classification addresses a learning problem where a decision-maker implements a classifier over agents who may manipulate their features in order to receive favorable pre…
How Many Domains Suffice for Domain Generalization? A Tight Characterization via the Domain Shattering Dimension
Cynthia Dwork, Lunjia Hu, Han Shao
We study a fundamental question of domain generalization: given a family of domains (i.e., data distributions), how many randomly sampled domains do we need to collect data from in…
A Machine Learning Theory Perspective on Strategic Litigation
Melissa Dutz, Han Shao, Avrim Blum +1
Strategic litigation involves bringing a case to court with the goal of having an impact beyond resolving the particular dispute at hand. In a common law system, one way a case may…