AbstractWe study the problem of matching applicants to jobs under one-sided preferences; that is, each applicant ranks a non-empty subset of jobs under an order of preference, possibly involving ties. A matching M is said to be more popular than T if the applicants that prefer M to T outnumber those that prefer T to M. A matching is said to be popular if there is no matching more popular than it. Equivalently, a matching M is popular if ϕ(M,T)≥ϕ(T,M) for all matchings T, where ϕ(X,Y) is the number of applicants that prefer X to Y.Previously studied solution concepts based on the popularity criterion are either not guaranteed to exist for every instance (e.g., popular matchings) or are NP-hard to compute (e.g., least unpopular matchings). Th...
Our input is a complete graph G = (V,E) on n vertices where each vertex has a strict ranking of all ...
We consider a matching problem in a bipartite graph $G=(A\cup B,E)$ where nodes in $A$ are agents ha...
AbstractIn this paper we consider the problem of computing an “optimal” popular matching. We assume ...
AbstractWe study the problem of matching applicants to jobs under one-sided preferences; that is, ea...
We study the problem of matching applicants to jobs under one-sided preferences: that is, each app...
We study the problem of matching applicants to jobs under one-sided preferences; that is, each appli...
We investigate the following problem: given a set of jobs and a set of people with preferences over ...
Matching problems arise in several real-world scenarios like assigning posts to applicants, houses t...
We consider the problem of matching a set of applicants to a set of posts, where each applicant has ...
An instance of the popular matching problem (POP-M) consists of a set of applicants and a set of pos...
We study the problem of matching a set of applicants to a set of posts, where each applicant has an ...
We consider the landscape of popular matchings in a bipartite graph G where every vertex has strict ...
We consider a matching problem in a bipartite graph G = (A ? B, E) where vertices have strict prefer...
AbstractWe consider the problem of matching people to items, where each person ranks a subset of ite...
We study dynamic matching problems in graphs among agents with preferences. Agents and/or edges of t...
Our input is a complete graph G = (V,E) on n vertices where each vertex has a strict ranking of all ...
We consider a matching problem in a bipartite graph $G=(A\cup B,E)$ where nodes in $A$ are agents ha...
AbstractIn this paper we consider the problem of computing an “optimal” popular matching. We assume ...
AbstractWe study the problem of matching applicants to jobs under one-sided preferences; that is, ea...
We study the problem of matching applicants to jobs under one-sided preferences: that is, each app...
We study the problem of matching applicants to jobs under one-sided preferences; that is, each appli...
We investigate the following problem: given a set of jobs and a set of people with preferences over ...
Matching problems arise in several real-world scenarios like assigning posts to applicants, houses t...
We consider the problem of matching a set of applicants to a set of posts, where each applicant has ...
An instance of the popular matching problem (POP-M) consists of a set of applicants and a set of pos...
We study the problem of matching a set of applicants to a set of posts, where each applicant has an ...
We consider the landscape of popular matchings in a bipartite graph G where every vertex has strict ...
We consider a matching problem in a bipartite graph G = (A ? B, E) where vertices have strict prefer...
AbstractWe consider the problem of matching people to items, where each person ranks a subset of ite...
We study dynamic matching problems in graphs among agents with preferences. Agents and/or edges of t...
Our input is a complete graph G = (V,E) on n vertices where each vertex has a strict ranking of all ...
We consider a matching problem in a bipartite graph $G=(A\cup B,E)$ where nodes in $A$ are agents ha...
AbstractIn this paper we consider the problem of computing an “optimal” popular matching. We assume ...