pith:KDYMTDIC
When and Why is Optimistic Multiplicative Weights Slow? The Geometry of Energy Dissipation
Optimistic multiplicative weights updates converge linearly in KL divergence to unique interior Nash equilibria in zero-sum games.
arxiv:2605.13242 v1 · 2026-05-13 · cs.GT · cs.LG
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Claims
we prove over the dual iterates that energy is dissipative, and by establishing tight bounds on the magnitude of dissipation, our analysis quantifies the geometric bottlenecks that arise when the corresponding primal iterates are close to the simplex boundary. This further translates into a new linear last-iterate convergence rate in KL divergence on games with a unique and interior Nash equilibrium... we prove this dependence is optimal.
The central analysis rests on viewing OMWU dual iterates as optimistic skew-gradient descent with respect to a specific energy function whose dissipation can be tightly bounded; if this modeling choice does not capture the dominant dynamics or if the energy function is not sufficiently dissipative under the stated conditions, the linear rate and optimality claims would not hold.
OMWU achieves linear last-iterate convergence in KL divergence for unique interior Nash equilibria with optimal game-constant dependence due to quantified energy dissipation, while uniform best-iterate rates exhibit constant lower bounds in KL and TV but improved O(T^{-1/2}) duality-gap rates in 2x2
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| First computed | 2026-05-18T02:44:49.496855Z |
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