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cs.GT2026
Algorithmic Asymmetry in Zero-Sum Games: Unilateral Recovery of Fast Convergence Against a Slow Opponent
James P. Bailey, Soham Das
Learning dynamics in zero-sum games are typically analyzed under algorithmic symmetry: both agents use the same update rule, or methods from a common algorithmic family. This is at…
cs.GT2026
Implicit Midpoint Gradient Descent: Fast and Learning rate free convergence for Zero-Sum Games
Gaoqi Xue, James P. Bailey
We study unconstrained bilinear zero-sum games, a fundamental model in online learning, adversarial optimization, and multi-agent decision-making. We introduce the implicit midpoin…