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We consider differentiable games where the goal is to find a Nash equilibrium. The machine learning community has recently started using variants of the gradient method (GD). Prime examples are extragradient (EG), the optimistic gradient…

Machine Learning · Computer Science 2020-07-08 Waïss Azizian , Ioannis Mitliagkas , Simon Lacoste-Julien , Gauthier Gidel

We study the problem of guaranteeing low regret in repeated games against an opponent with unknown membership in one of several classes. We add the constraint that our algorithm is non-exploitable, in that the opponent lacks an incentive to…

Computer Science and Game Theory · Computer Science 2022-07-05 Anthony DiGiovanni , Ambuj Tewari

We study hedonic coalition formation games in which cooperation among the players is restricted by a graph structure: a subset of players can form a coalition if and only if they are connected in the given graph. We investigate the…

Computer Science and Game Theory · Computer Science 2016-03-22 Ayumi Igarashi , Edith Elkind

Evaluating and optimizing policies in the presence of unobserved confounders is a problem of growing interest in offline reinforcement learning. Using conventional methods for offline RL in the presence of confounding can not only lead to…

Machine Learning · Statistics 2023-11-08 Chinmaya Kausik , Yangyi Lu , Kevin Tan , Maggie Makar , Yixin Wang , Ambuj Tewari

We investigate the local linear convergence properties of the Alternating Direction Method of Multipliers (ADMM) when applied to Semidefinite Programming (SDP). A longstanding belief suggests that ADMM is only capable of solving SDPs to…

Optimization and Control · Mathematics 2026-05-19 Shucheng Kang , Xin Jiang , Heng Yang

In classical complexity theory, the two definitions of probabilistically checkable proofs -- the constraint satisfaction and the nonlocal games version -- are computationally equal in power. In the quantum setting, the situation is far less…

Quantum Physics · Physics 2024-03-21 Anand Natarajan , Chinmay Nirkhe

Decision making in modern large-scale and complex systems such as communication networks, smart electricity grids, and cyber-physical systems motivate novel game-theoretic approaches. This paper investigates big strategic (non-cooperative)…

Computer Science and Game Theory · Computer Science 2016-09-22 Tansu Alpcan , Benjamin I. P. Rubinstein , Christopher Leckie

Many recent AI architectures are inspired by zero-sum games, however, the behavior of their dynamics is still not well understood. Inspired by this, we study standard gradient descent ascent (GDA) dynamics in a specific class of non-convex…

Optimization and Control · Mathematics 2021-01-14 Lampros Flokas , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Georgios Piliouras

The inner alignment problem, which asserts whether an arbitrary artificial intelligence (AI) model satisfices a non-trivial alignment function of its outputs given its inputs, is undecidable. This is rigorously proved by Rice's theorem,…

We show undecidability of the satisfiability problem of what is arguably the simplest non-sub-Boolean modal logic with an implicit notion of binding. This work enriches the series of existing results of undecidability of modal logics with…

Logic in Computer Science · Computer Science 2015-08-18 Guillaume Hoffmann

In the setting of a self-dual cone in a finite-dimensional inner product space, we consider (zero-sum) linear games. In our previous work, we showed that a Z-transformation with positive value is completely mixed. The present paper…

Optimization and Control · Mathematics 2024-05-08 Muddappa Seetharama Gowda

Generalized trust-region subproblem (GT) is a nonconvex quadratic optimization with a single quadratic constraint. It reduces to the classical trust-region subproblem (T) if the constraint set is a Euclidean ball. (GT) is polynomially…

Optimization and Control · Mathematics 2021-09-14 Jiulin Wang , Mengmeng Song , Yong Xia

We consider the dynamic behavior of several variants of the Network Creation Game, introduced by Fabrikant et al. [PODC'03]. Equilibrium networks in these models have desirable properties like low social cost and small diameter, which makes…

Computer Science and Game Theory · Computer Science 2013-05-29 Bernd Kawald , Pascal Lenzner

Anomaly detection is a method for discovering unusual and suspicious behavior. In many real-world scenarios, the examined events can be directly linked to the actions of an adversary, such as attacks on computer networks or frauds in…

Machine Learning · Computer Science 2020-04-23 Olga Petrova , Karel Durkota , Galina Alperovich , Karel Horak , Michal Najman , Branislav Bosansky , Viliam Lisy

We identify a subproblem of the model-checking problem for the epistemic \mu-calculus which is decidable. Formulas in the instances of this subproblem allow free variables within the scope of epistemic modalities in a restricted form that…

Computer Science and Game Theory · Computer Science 2013-10-28 Rodica Bozianu , Catalin Dima , Constantin Enea

In this paper, we introduce post-selection games, a generalization of nonlocal games where each round can be not only won or lost by the players, but also discarded by the referee. Such games naturally formalize possibilistic proofs of…

Quantum Physics · Physics 2026-02-10 Víctor Calleja Rodríguez , Ivan A. Bocanegra-Garay , Mateus Araújo

Extended non-local games are a generalization of monogamy-of-entanglement games, played by two quantum parties and a quantum referee that performs a measurement on their local quantum system. Along the lines of the NPA hierarchy, the…

Quantum Physics · Physics 2025-04-23 Llorenç Escolà-Farràs , Florian Speelman

We study online learning in two-player uninformed Markov games, where the opponent's actions and policies are unobserved. In this setting, Tian et al. (2021) show that achieving no-external-regret is impossible without incurring an…

Machine Learning · Computer Science 2026-02-10 Junyan Liu , Haipeng Luo , Zihan Zhang , Lillian J. Ratliff

We use a recently discovered constrained de Finetti reduction (aka "Post-Selection Lemma") to study the parallel repetition of multi-player non-local games under no-signalling strategies. Since the technique allows us to reduce general…

Quantum Physics · Physics 2016-10-04 Cécilia Lancien , Andreas Winter

Wide machine learning tasks can be formulated as non-convex multi-player games, where Nash equilibrium (NE) is an acceptable solution to all players, since no one can benefit from changing its strategy unilaterally. Attributed to the…

Computer Science and Game Theory · Computer Science 2023-01-20 Guanpu Chen , Gehui Xu , Fengxiang He , Yiguang Hong , Leszek Rutkowski , Dacheng Tao
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