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Discrete convex functions are used in many areas, including operations research, discrete-event systems, game theory, and economics. The objective of this paper is to offer a survey on fundamental operations for various kinds of discrete…

Combinatorics · Mathematics 2019-10-04 Kazuo Murota

Integrally convex functions constitute a fundamental function class in discrete convex analysis, including M-convex functions, L-convex functions, and many others. This paper aims at a rather comprehensive survey of recent results on…

Combinatorics · Mathematics 2023-02-23 Kazuo Murota , Akihisa Tamura

Discrete convex functions are used in many areas, including operations research, discrete-event systems, game theory, and economics. The objective of this paper is to investigate basic operations such as direct sum, splitting, and…

Optimization and Control · Mathematics 2020-08-31 Kazuo Murota

We study the problem of characterizing the set of games that are consistent with observed equilibrium play. Our contribution is to develop and analyze a new methodology based on convex optimization to address this problem for many classes…

Computer Science and Game Theory · Computer Science 2017-03-23 Juba Ziani , Venkat Chandrasekaran , Katrina Ligett

In several recent papers some concepts of convex analysis were extended to discrete sets. This paper is one more step in this direction. It is well known that a local minimum of a convex function is always its global minimum. We study some…

Combinatorics · Mathematics 2024-02-05 Vladimir Gurvich , Mariya Naumova

Traditional solvable game theory and mean-field-type game theory (risk-aware games) predominantly focus on quadratic costs due to their analytical tractability. Nevertheless, they often fail to capture critical non-linearities inherent in…

Optimization and Control · Mathematics 2025-05-09 Julian Barreiro-Gomez , Tyrone E. Duncan , Bozenna Pasik-Duncan , Hamidou Tembine

In discrete convex analysis, various convexity concepts are considered for discrete functions such as separable convexity, L-convexity, M-convexity, integral convexity, and multimodularity. These concepts of discrete convex functions are…

Combinatorics · Mathematics 2023-02-06 Satoko Moriguchi , Kazuo Murota

Equilibrium in Economics has been seldom addressed in a situation where some variables are discrete. This work introduces a problem related to lot-sizing with several players, and analyses some strategies which are likely to be found in…

Computer Science and Game Theory · Computer Science 2016-04-28 João Pedro Pedroso , Yves Smeers

Independent set games are cooperative games defined on graphs, where players are edges and the value of a coalition is the maximum cardinality of independent sets in the subgraph defined by the coalition. In this paper, we investigate the…

Discrete Mathematics · Computer Science 2020-09-14 Han Xiao , Yuanxi Wang , Qizhi Fang

Convexity is an important notion in non linear optimization theory as well as in infinite dimensional functional analysis. As will be seen below, very simple and powerful tools will be derived from elementary duality arguments (which are…

Functional Analysis · Mathematics 2020-04-21 Guy Bouchitte

The study of convex functions - in particular, of their optimization (really minimization) is one of the most important fields of applied mathematics. Convexity seems to be one of those incredibly well-chosen hypotheses which is just…

Optimization and Control · Mathematics 2026-03-11 Eigil Fjeldgren Rischel

Dynamic noncooperative game theory is a field of mathematics and economics in which a lot of research is being carried out at present featuring a great number of applications in many different areas of economics and management science like…

Optimization and Control · Mathematics 2014-09-19 Philipp Hungerländer

Using results from convex analysis, we investigate a novel approach to identification and estimation of discrete choice models which we call the Mass Transport Approach (MTA). We show that the conditional choice probabilities and the…

Econometrics · Economics 2021-02-17 Khai Xiang Chiong , Alfred Galichon , Matt Shum

This paper considers a class of generalized convex games where each player is associated with a convex objective function, a convex inequality constraint and a convex constraint set. The players aim to compute a Nash equilibrium through…

Optimization and Control · Mathematics 2015-09-23 Minghui Zhu , Emilio Frazzoli

Continuous-time empirical dynamic discrete choice games offer notable computational advantages over discrete-time models. This paper addresses remaining computational and econometric challenges to further improve both model solution and…

Econometrics · Economics 2025-11-11 Jason R. Blevins

We develop a convex analysis approach for solving LQG optimal control problems and apply it to major-minor (MM) LQG mean-field game (MFG) systems. The approach retrieves the best response strategies for the major agent and all minor agents…

Systems and Control · Computer Science 2020-06-15 Dena Firoozi , Sebastian Jaimungal , Peter E. Caines

We derive new prox-functions on the simplex from additive random utility models of discrete choice. They are convex conjugates of the corresponding surplus functions. In particular, we explicitly derive the convexity parameter of discrete…

Optimization and Control · Mathematics 2019-09-13 David Müller , Yurii Nesterov , Vladimir Shikhman

We introduce the notions of weakly *-concave and weakly naturally quasi-concave correspondence and prove fixed point theorems and continuous selection theorems for these kind of correspondences. As applications in the game theory, by using…

Optimization and Control · Mathematics 2013-03-29 Monica Patriche

Convexity, though extremely important in mathematical programming, has not drawn enough attention in the field of dynamic programming. This paper gives conditions for verifying convexity of the cost-to-go functions, and introduces an…

Optimization and Control · Mathematics 2011-11-14 Sheng Yu , Enrique Campos-Nanez

Adversarial training, a special case of multi-objective optimization, is an increasingly prevalent machine learning technique: some of its most notable applications include GAN-based generative modeling and self-play techniques in…

Machine Learning · Statistics 2021-03-17 Gauthier Gidel , David Balduzzi , Wojciech Marian Czarnecki , Marta Garnelo , Yoram Bachrach
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