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The stable allocation problem is a many-to-many generalization of the well-known stable marriage problem, where we seek a bipartite assignment between, say, jobs (of varying sizes) and machines (of varying capacities) that is "stable" based…

Data Structures and Algorithms · Computer Science 2014-11-26 Ágnes Cseh , Brian C. Dean

We prove a motivic stabilization result for the cohomology of the local systems on configuration spaces of varieties over $\mathbb{C}$ attached to character polynomials. Our approach interprets the stabilization as a probabilistic…

Algebraic Geometry · Mathematics 2020-12-16 Sean Howe

We say that an algorithm is stable if small changes in the input result in small changes in the output. This kind of algorithm stability is particularly relevant when analyzing and visualizing time-varying data. Stability in general plays…

Data Structures and Algorithms · Computer Science 2025-03-10 Wouter Meulemans , Bettina Speckmann , Kevin Verbeek , Jules Wulms

Leveraging tools from the study of linear fractional transformations and algebraic Riccati equations, a local characterization of consistent conjectural variations equilibrium is given for two player games on continuous action spaces with…

Computer Science and Game Theory · Computer Science 2023-06-07 Daniel J. Calderone , Benjamin J. Chasnov , Samuel A. Burden , Lillian J. Ratliff

We propose a generalization of the classical stable marriage problem. In our model, the preferences on one side of the partition are given in terms of arbitrary binary relations, which need not be transitive nor acyclic. This generalization…

Computer Science and Game Theory · Computer Science 2014-07-28 Linda Farczadi , Konstantinos Georgiou , Jochen Könemann

Two-sided matching markets describe a large class of problems wherein participants from one side of the market must be matched to those from the other side according to their preferences. In many real-world applications (e.g. content…

Computer Science and Game Theory · Computer Science 2024-10-16 Hadi Hosseini , Sanjukta Roy , Duohan Zhang

Stability is a central property in learning and statistics promising the output of an algorithm $A$ does not change substantially when applied to similar datasets $S$ and $S'$. It is an elementary fact that any sufficiently stable algorithm…

Machine Learning · Computer Science 2025-02-13 Max Hopkins , Shay Moran

The stable marriage problem, as addressed by Gale and Shapely [1] consists of providing a bipartite matching between n " boys " and n " girls "-each of whom have a totally ordered preference list over the other set-such that there exists no…

Computer Science and Game Theory · Computer Science 2016-08-30 Mircea Adrian Digulescu

The concept of sequential choice functions is introduced and studied. This concept applies to the reduction of the problem of stable matchings with sequential workers to a situation where the workers are linear.

Combinatorics · Mathematics 2024-03-26 Vladimir I. Danilov

A tournament is \emph{acyclically indecomposable} if no acyclic autonomous set of vertices has more than one element. We identify twelve infinite acyclically indecomposable tournaments and prove that every infinite acyclically…

Combinatorics · Mathematics 2008-01-29 Youssef Boudabbous , Maurice Pouzet

In this article, we study feature attributions of Machine Learning (ML) models originating from linear game values and coalitional values defined as operators on appropriate functional spaces. The main focus is on random games based on the…

Computer Science and Game Theory · Computer Science 2024-08-13 Alexey Miroshnikov , Konstandinos Kotsiopoulos , Khashayar Filom , Arjun Ravi Kannan

We call a partition of a $c$-partite tournament into tournaments of order $c$ is strong if each tournament is strongly connected. The strong partition number denoted as $ST(r)$, represents the minimum integer $c'$ such that every regular…

Combinatorics · Mathematics 2024-03-14 Jiangdong Ai , Fankang He , Yihang Liu

In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too…

Machine Learning · Computer Science 2007-05-23 Shane Legg , Marcus Hutter , Akshat Kumar

We consider a class of deterministic mean field games, where the state associated with each player evolves according to an ODE which is linear w.r.t. the control. Existence, uniqueness, and stability of solutions are studied from the point…

Optimization and Control · Mathematics 2022-10-27 Alberto Bressan , Khai T. Nguyen

We survey the design of elections that are resilient to attempted interference by third parties. For example, suppose votes have been cast in an election between two candidates, and then each vote is randomly changed with a small…

Probability · Mathematics 2021-07-13 Steven Heilman

One of the basic properties of a queueing network is stability. Roughly speaking, it is the property that the total number of jobs in the network remains bounded as a function of time. One of the key questions related to the stability issue…

Probability · Mathematics 2009-11-19 David Gamarnik , Dmitriy Katz

Tournaments are a widely used mechanism to rank alternatives in a noisy environment. This paper investigates a fundamental issue of economics in tournament design: what is the best usage of limited resources, that is, how should the…

Applications · Statistics 2022-05-24 Balázs R. Sziklai , Péter Biró , László Csató

This article aims to investigate sufficient conditions for the stability of stochastic differential equations with a random structure, particularly in contexts involving the presence of concentration points. The proof of asymptotic…

Probability · Mathematics 2023-05-22 Taras Lukashiv , Igor V. Malyk , Maryna Chepeleva , Petr V. Nazarov

Rankings are ubiquitous across many applications, from search engines to hiring committees. In practice, many rankings are derived from the output of predictors. However, when predictors trained for classification tasks have intrinsic…

Machine Learning · Computer Science 2024-02-15 Siddartha Devic , Aleksandra Korolova , David Kempe , Vatsal Sharan

In this paper, we examine the long-run behavior of regularized, no-regret learning in finite games. A well-known result in the field states that the empirical frequencies of no-regret play converge to the game's set of coarse correlated…

Computer Science and Game Theory · Computer Science 2023-11-07 Victor Boone , Panayotis Mertikopoulos
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