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Home/Authors/Gabriele Farina

Gabriele Farina

Topic trends: 32,543 papers · similarity ≥ 0.4 · year ≥ 2024 · Data sourced from Semantic Scholar

34,598 papers | Abstracts: 31,650 (91.5%) | Citations: 34,598 (100.0%) | arXiv: 26,074 (75.4%)

Built: Feb 14, 2026, 11:22 PM AMS

21

papers

273

total citations

papers (21)

No-Regret Learning Dynamics for Extensive-Form Correlated Equilibrium

NEURIPS 2020arXiv

Uncoupled Learning Dynamics with $O(\log T)$ Swap Regret in Multiplayer Games

NEURIPS 2022arXiv

The Consensus Game: Language Model Generation via Equilibrium Search

Near-Optimal No-Regret Learning Dynamics for General Convex Games

NEURIPS 2022arXiv

On the Convergence of No-Regret Learning Dynamics in Time-Varying Games

NEURIPS 2023arXiv

Polynomial-Time Computation of Optimal Correlated Equilibria in Two-Player Extensive-Form Games with Public Chance Moves and Beyond

NEURIPS 2020arXiv

Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games

NEURIPS 2023arXiv

Regret Matching+: (In)Stability and Fast Convergence in Games

NEURIPS 2023arXiv

Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games

NEURIPS 2023arXiv

Optimistic Mirror Descent Either Converges to Nash or to Strong Coarse Correlated Equilibria in Bimatrix Games

NEURIPS 2022arXiv

Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games

The Update-Equivalence Framework for Decision-Time Planning

Efficient Learning in Polyhedral Games via Best-Response Oracles

A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence

Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence beyond the Minty Property

Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games

Efficient Kernelized Learning in Polyhedral Games beyond Full Information: From Colonel Blotto to Congestion Games

NEURIPS 2025arXiv

On the Universal Near Optimality of Hedge in Combinatorial Settings

NEURIPS 2025arXiv

Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning

Equilibrium Refinement for the Age of Machines: The One-Sided Quasi-Perfect Equilibrium

Subgame Solving in Adversarial Team Games