1 citations · 1 across the 7 of their papers we have counts for
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Linear Last-Iterate Convergence Rates for Optimistic Learning in Harmonic Games
John Lazarsfeld, Anas Barakat, Jacob Abernethy +4
We prove that the last iterate of Optimistic Follow-The-Regularized-Leader (OFTRL) converges at a linear rate to a Nash equilibrium in multiplayer harmonic games. Our result holds…
Learning in Continuous Games from Pairwise Preference Feedback
Anas Barakat
We study learning in continuous games when players receive only pairwise preference feedback, revealing which of two actions is preferred but neither payoff values nor preference m…
Online Learning on Hidden-Convex Losses via Algorithmic Equivalence: Optimal Regret, Geometric Barrier, and Bandit Feedback
Anas Barakat, Andreas Kontogiannis, Vasilis Pollatos +2
We study adversarial online learning with hidden-convex losses, i.e., nonconvex losses that become convex after a nonlinear reparameterization. Ghai, Lu and Hazan (2022) proved tha…
When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation
John Lazarsfeld, Anas Barakat, Georgios Piliouras +2
This paper studies the convergence of the Optimistic Multiplicative Weights Update algorithm (OMWU) in two player zero-sum games. Recent works have identified instances on which th…
Prompt Interference in LLM Post-Training: Why Pass@k Optimization Can Degrade Pass@1
Anas Barakat, Souradip Chakraborty, Khushbu Pahwa +1
Pass@ is a widely used performance metric for verifiable large language model tasks, including mathematical reasoning, code generation, and short-answer reasoning. It defines su…