Optimization, Learning, and Game Theory 

The Optimization, Learning, and Game Theory Workshop is a one-day event that brings together researchers working at the intersection of optimization, machine learning, game theory, and related fields. The workshop aims to foster the exchange of ideas between communities by highlighting recent advances in both the theoretical foundations and practical applications of these areas.

The scientific program features invited talks by leading researchers, providing a broad perspective on current developments in learning dynamics, multi-agent systems, equilibrium computation, online learning, and optimization methods for games and decision-making. The workshop will also include a panel discussion, offering opportunities for interaction, open questions, and future research directions.

The workshop is intended for researchers, faculty, postdoctoral scholars, and graduate students interested in the mathematical and algorithmic foundations of learning and optimization, as well as their applications to economics, artificial intelligence, operations research, and beyond. Throughout the day, ample time will be provided for discussions and informal networking to encourage new collaborations across disciplines.