Gabriele Farina
Assistant Professor
Develops foundations for learning and decision-making under imperfect information, combining game theory with machine learning and optimization for equilibrium computation.
Gabriele Farina's lab at MIT works on learning theory & optimization and reinforcement learning. 52 papers since 2023, 47 at top venues, mostly NeurIPS and ICLR. Applications close .
At a glance
- papers, 2023–2026
- 14/ year
- at T1 venues
- 90%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 14 papers2026 · T1 12 · collecting
- 15 papers2025 · T1 13
- 13 papers2024 · T1 12
- 10 papers2023 · T1 10
T1 venuesOtherVenues: NeurIPS, ICLR, EC, COLT, ICML
Research focuspaper titles that use each topic's words
- Learning theory & optimization19 papers
- Reinforcement learning18 papers
- imperfect5 papers
- develops foundations0 papers
- game theory0 papers
Paper list
From the lab homepage.
202614 papers
- FOCS (T1)A Polynomial-Time Algorithm for Variational Inequalities under the Minty Condition
- FOCS (T1)A Unifying Framework for Quasi-Polynomial Optimization of Fixed-degree Polynomials
- ICLR (T1)Computing Equilibrium beyond Unilateral Deviation (opens in a new tab)
- COLT (T1)Defensive Generation
- ICLR (T1)Differentially Private Equilibrium Finding in Polymatrix Games (opens in a new tab)
- Artificial Intelligence (T1)Efficient Representations for Team and Imperfect-Recall Equilibrium Computation
- EC (T1)Equilibrium with Internal Transfer
- EC (T1)Improved Hardness Results for Min-Max Optimization with Coupled Constraints
- ICLR (T1)Learning Correlated Reward Models: Statistical Barriers and Opportunities (opens in a new tab)
- ICLR (T1)Online Learning and Equilibrium Computation with Ranking Feedback (opens in a new tab)
- ICLR (T1)Reevaluating Policy Gradient Methods for Imperfect-Information Games (opens in a new tab)
- Oper. Res.Separation of non-ergodic uniform convergence rates for regularized learning in games
202515 papers
- ICLR (T1)A Policy-Gradient Approach to Solving Imperfect-Information Games with Best-Iterate Convergence (opens in a new tab)
- Oper. Res.Better Regularization for Sequential Decision Spaces: Fast Convergence Rates for Nash, Correlated, and Team Equilibria (opens in a new tab)
- EC (T1)Cautious Optimism: A Meta-Algorithm for Near-Constant Regret in General Games (opens in a new tab)
- NeurIPS (T1)Efficient Kernelized Learning in Polyhedral Games beyond Full Information: From Colonel Blotto to Congestion Games (opens in a new tab)
- STOC (T1)Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games (opens in a new tab)
- COLT (T1)Efficient Near-Optimal Algorithm for Online Shortest Paths in Directed Acyclic Graphs with Bandit Feedback Against Adaptive Adversaries (opens in a new tab)
- ICML (T1)Expected Variational Inequalities (opens in a new tab)
- STOC (T1)Faster Rates for No-Regret Learning in General Games via Cautious Optimism (opens in a new tab)
- ICLR (T1)Last-Iterate Convergence Properties of Regret-Matching Algorithms in Games (opens in a new tab)
- EC (T1)Learning and Computation of Φ-Equilibria at the Frontier of Tractability (opens in a new tab)
- NeurIPS (T1)On the Universal Near Optimality of Hedge in Combinatorial Settings (opens in a new tab)
- Math. of OROptimal Correlated Equilibria in General-Sum Extensive-Form Games: Fixed-Parameter Algorithms, Hardness, and Two-Sided Column-Generation (opens in a new tab)
202413 papers
- GameSecContested Logistics: A Game-Theoretic Approach (opens in a new tab)
- NeurIPS (T1)Efficient $\Phi$-Regret Minimization with Low-Degree Swap Deviations in Extensive-Form Games (opens in a new tab)
- AAAI (T1)Efficient Online Learning on Polytopes with Linear Minimization Oracles (opens in a new tab)
- NeurIPS (T1)Fast Last-Iterate Convergence of Learning in Games Requires Forgetful Algorithms (opens in a new tab)
- EC (T1)Hidden-Role Games: Equilibrium Concepts and Computation (opens in a new tab)
- ICLR (T1)Mediator Interpretation and Faster Learning Algorithms for Linear Correlated Equilibria in General Sequential Games (opens in a new tab)
- NeurIPS (T1)On the Optimality of Dilated Entropy and Lower Bounds for Online Learning in Extensive-Form Games (opens in a new tab)
- AAAI (T1)Optimistic Policy Gradient in Multi-Player Markov Games with a Single Controller: Convergence Beyond the Minty Property (opens in a new tab)
- NeurIPS (T1)Polynomial-Time Computation of Exact $\Phi$-Equilibria in Polyhedral Games (opens in a new tab)
- NAACL (T1)Regularized Conventions: Equilibrium Computation as a Model of Pragmatic Reasoning (opens in a new tab)
- EC (T1)Steering No-Regret Learners to a Desired Equilibrium (opens in a new tab)
- ICLR (T1)The Consensus Game: Language Model Generation via Equilibrium Search (opens in a new tab)
202310 papers
- NeurIPS (T1)Computing Optimal Equilibria and Mechanisms via Learning in Zero-Sum Extensive-Form Games (opens in a new tab)
- ICLR (T1)ESCHER: Eschewing Importance Sampling in Games by Computing a History Value Function to Estimate Regret (opens in a new tab)
- ICLR (T1)Mastering the Game of No-Press Diplomacy via Human-Regularized Reinforcement Learning and Planning (opens in a new tab)
- ICLR (T1)Meta-Learning in Games (opens in a new tab)
- ICML (T1)Near-Optimal $\Phi$-Regret Learning in Extensive-Form Games (opens in a new tab)
- NeurIPS (T1)On the Convergence of No-Regret Learning Dynamics in Time-Varying Games (opens in a new tab)
- NeurIPS (T1)Polynomial-Time Linear-Swap Regret Minimization in Imperfect-Information Sequential Games (opens in a new tab)
- NeurIPS (T1)Regret Matching$^+$: (In)Stability and Fast Convergence in Games (opens in a new tab)
- ICML (T1)Team Belief DAG: Generalizing the Sequence Form to Team Games for Fast Computation of Correlated Team Max-Min Equilibria via Regret Minimization (opens in a new tab)
- NeurIPS (T1)Team-PSRO for Learning Approximate TMECor in Large Team Games via Cooperative Reinforcement Learning (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to MITFall 2027
MIT EECS Computer Science PhD
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