2 citations · 2 across the 2 of their papers we have counts for
4 papers
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…
Probably Approximately Precision and Recall Learning
Lee Cohen, Yishay Mansour, Shay Moran +1
Precision and Recall are fundamental metrics in machine learning tasks where both accurate predictions and comprehensive coverage are essential, such as in multi-label learning, la…