The paper establishes Contr-hardness for correlated equilibria in concave quadratic games, an exponential lower bound on swap regret minimization, and FPTAS algorithms for poly-dimensional Φ-equilibria in concave games.
Polynomial-time linear-swap regret minimiza- tion in imperfect-information sequential games
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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UNVERDICTED 2representative citing papers
Black-box reductions from no-regret online learning to multicalibration and from multicalibration to Phi-regret minimization are established, resolving the main open question in Garg et al. (SODA '24).
citing papers explorer
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On the Complexity of Correlated Equilibria Beyond Normal-Form Games
The paper establishes Contr-hardness for correlated equilibria in concave quadratic games, an exponential lower bound on swap regret minimization, and FPTAS algorithms for poly-dimensional Φ-equilibria in concave games.
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An Efficient Black-Box Reduction from Online Learning to Multicalibration, and a New Route to $\Phi$-Regret Minimization
Black-box reductions from no-regret online learning to multicalibration and from multicalibration to Phi-regret minimization are established, resolving the main open question in Garg et al. (SODA '24).