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A structured variable selection problem is considered in which the covariates, divided into predefined groups, activate according to sparse patterns with few nonzero entries per group. Capitalizing on the concept of atomic norm, a composite…

机器学习 · 计算机科学 2023-11-03 David Gregoratti , Xavier Mestre , Carlos Buelga

In this paper, we study a model of network formation in large populations. Each agent can choose the strength of interaction (i.e. connection) with other agents to find a Nash equilibrium. Different from the recently-developed theory of…

最优化与控制 · 数学 2025-08-07 Gokce Dayanikli , Mathieu Lauriere

Three essential criteria are important for activity planning, including: (1) finding a group of attendees familiar with the initiator, (2) ensuring each attendee in the group to have tight social relations with most of the members in the…

社会与信息网络 · 计算机科学 2011-04-19 De-Nian Yang , Yi-Ling Chen , Wang-Chien Lee , Ming-Syan Chen

We investigate complexity issues related to pure Nash equilibria of strategic games. We show that, even in very restrictive settings, determining whether a game has a pure Nash Equilibrium is NP-hard, while deciding whether a game has a…

计算机科学与博弈论 · 计算机科学 2013-07-19 G. Gottlob , G. Greco , F. Scarcello

Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

计算机科学与博弈论 · 计算机科学 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

In the classical Binary Networked Public Goods (BNPG) game, a player can either invest in a public project or decide not to invest. Based on the decisions of all the players, each player receives a reward as per his/her utility function.…

计算机科学与博弈论 · 计算机科学 2024-01-03 Arnab Maiti , Palash Dey

In this paper, we examine the Nash equilibrium convergence properties of no-regret learning in general N-player games. For concreteness, we focus on the archetypal follow the regularized leader (FTRL) family of algorithms, and we consider…

计算机科学与博弈论 · 计算机科学 2021-02-05 Angeliki Giannou , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Panayotis Mertikopoulos

The property of the communication network and the constraints on the strategic space are two factors that determine the complexity of the distributed Nash equilibrium (DNE) seeking problem. The DNE seeking problem of aggregative games has…

最优化与控制 · 数学 2025-02-26 Zhaocong Liu , Jie Huang

In this work, we investigate the distributed generalized Nash equilibrium (GNE) seeking problems for $N$-coalition games with inequality constraints. First, we study the scenario where each agent in a coalition has full information of all…

最优化与控制 · 数学 2021-09-28 Chao Sun , Guoqiang Hu

We consider Group Control by Adding Individuals (GCAI) in the setting of group identification for two procedural rules -- the consensus-start-respecting rule and the liberal-start-respecting rule. It is known that GCAI for both rules are…

计算机科学与博弈论 · 计算机科学 2023-01-30 Yongjie Yang , Dinko Dimitrov

Consider an undirected graph modeling a social network, where the vertices represent users, and the edges do connections among them. In the competitive diffusion game, each of a number of players chooses a vertex as a seed to propagate…

Atomic congestion games are a classic topic in network design, routing, and algorithmic game theory, and are capable of modeling congestion and flow optimization tasks in various application areas. While both the price of anarchy for such…

计算机科学与博弈论 · 计算机科学 2024-10-23 Cornelius Brand , Robert Ganian , Subrahmanyam Kalyanasundaram , Fionn Mc Inerney

Fueled by algorithmic advances, AI algorithms are increasingly being deployed in settings subject to unanticipated challenges with complex social effects. Motivated by real-world deployment of AI driven, social-network based suicide…

We study the computational complexity of finding stable outcomes in hedonic games, which are a class of coalition formation games. We restrict our attention to symmetric additively-separable hedonic games, which are a nontrivial subclass of…

计算机科学与博弈论 · 计算机科学 2015-09-18 Martin Gairing , Rahul Savani

Friendship prediction is an important task in social network analysis (SNA). It can help users identify friends and improve their level of activity. Most previous approaches predict users' friendship based on their historical records, such…

社会与信息网络 · 计算机科学 2014-02-18 Erheng Zhong , Evan Wei Xiang , Wei Fan , Nathan Nan Liu , Qiang Yang

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…

计算机科学与博弈论 · 计算机科学 2013-05-29 Bernd Kawald , Pascal Lenzner

Additively separable hedonic games (ASHGs) are a prominent model of coalition formation where agents' preferences are derived from their individual valuations of peers. While social welfare maximization in ASHGs has traditionally focused…

计算机科学与博弈论 · 计算机科学 2026-05-20 Marta Pagano , Alexander Schlenga

In graph modification problems, one is given a graph G and the goal is to apply a minimum number of modification operations (such as edge deletions) to G such that the resulting graph fulfills a certain property. For example, the Cluster…

数据结构与算法 · 计算机科学 2016-06-13 Christian Komusiewicz , André Nichterlein , Rolf Niedermeier

We continue and extend previous work on the parameterized complexity analysis of the NP-hard Stable Roommates with Ties and Incomplete Lists problem, thereby strengthening earlier results both on the side of parameterized hardness as well…

计算复杂性 · 计算机科学 2021-03-09 Robert Bredereck , Klaus Heeger , Dušan Knop , Rolf Niedermeier

A fundamental shortcoming of the concept of Nash equilibrium is its computational intractability: approximating Nash equilibria in normal-form games is PPAD-hard. In this paper, inspired by the ideas of smoothed analysis, we introduce a…

计算机科学与博弈论 · 计算机科学 2024-07-23 Constantinos Daskalakis , Noah Golowich , Nika Haghtalab , Abhishek Shetty