3 papers
cs.LG2025
On the Limitations and Possibilities of Nash Regret Minimization in Zero-Sum Matrix Games under Noisy Feedback
Arnab Maiti, Kevin Jamieson, Lillian J. Ratliff
This paper studies a variant of two-player zero-sum matrix games, where, at each timestep, the row player selects row , the column player selects column , and the row player…
cs.LG2024
Online SuBmodular + SuPermodular (BP) Maximization with Bandit Feedback
Adhyyan Narang, Omid Sadeghi, Lillian J Ratliff +2
In the context of online interactive machine learning with combinatorial objectives, we extend purely submodular prior work to more general non-submodular objectives. This includes…
cs.LG2024
Emergent specialization from participation dynamics and multi-learner retraining
Sarah Dean, Mihaela Curmei, Lillian J. Ratliff +2
Numerous online services are data-driven: the behavior of users affects the system's parameters, and the system's parameters affect the users' experience of the service, which in t…