2 papers
cs.LG2025
Online Mixture of Experts: No-Regret Learning for Optimal Collective Decision-Making
Larkin Liu, Jalal Etesami
We explore the use of expert-guided bandit learning, which we refer to as online mixture-of-experts (OMoE). In this setting, given a context, a candidate committee of experts must…
cs.LG2025
Riemannian Manifold Learning for Stackelberg Games with Neural Flow Representations
Larkin Liu, Kashif Rasul, Yutong Chao +1
We present a novel framework for online learning in Stackelberg general-sum games, where two agents, the leader and follower, engage in sequential turn-based interactions. At the c…