Mixed Nash Equilibria in the Adversarial Examples Game
Publications associées (37)
Graph Chatbot
Chattez avec Graph Search
Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.
AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.
Many important problems in contemporary machine learning involve solving highly non- convex problems in sampling, optimization, or games. The absence of convexity poses significant challenges to convergence analysis of most training algorithms, and in some ...
To quantify a player's commitment in a given Nash equilibrium of a finite dynamic game, we map the corresponding normal-form game to a "canonical extension," which allows each player to adjust his or her move with a certain probability. The commitment meas ...
We study a robust monopoly pricing problem with a minimax regret objective, where a seller endeavors to sell multiple goods to a single buyer, only knowing that the buyer's values for the goods range over a rectangular uncertainty set. We interpret this pr ...
We consider robust optimization problems, where the goal is to optimize an unknown objective function against the worst-case realization of an uncertain parameter. For this setting, we design a novel sample-efficient algorithm GP-MRO, which sequentially le ...
In this paper we provide a novel and simple algorithm, Clairvoyant Multiplicative Weights Updates (CMWU), for convergence to \textit{Coarse Correlated Equilibria} (CCE) in general games. CMWU effectively corresponds to the standard MWU algorithm but where ...
We address online bandit learning of Nash equilibria in multi-agent convex games. We propose an algorithm whereby each agent uses only obtained values of her cost function at each joint played action, lacking any information of the functional form of her c ...
Oligopolistic competition occurs often in transportation as well as in other markets due to reasons such as barriers to entry, limited capacity of the infrastructure and external regulations. In transport oligopolies, suppliers are profit maximizers and ta ...
We consider multiagent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we propose a novel dis ...
In this paper, we introduce a model of a financial market as a multiagent repeated game where the players are market makers. We formalize the concept of market making and the parameters of the game. Our main contribution is a framework that combines game t ...
We reconsider the training objective of Generative Adversarial Networks (GANs) from the mixed Nash Equilibria (NE) perspective. Inspired by the classical prox methods, we develop a novel algorithmic framework for GANs via an infinite-dimensional two-player ...