T Kavitha, J Mestre, M Nasre - Theoretical Computer Science, 2011 - Elsevier
We 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 …
An input to the Popular Matching problem, in the roommates setting (as opposed to the marriage setting), consists of a graph G (not necessarily bipartite) where each vertex ranks …
We study social welfare in one-sided matching markets where the goal is to efficiently allocate n items to n agents that each have a complete, private preference list and a unit …
We consider the problem of finding a popular matching in the Weighted Capacitated House Allocation problem (WCHA). An instance of WCHA involves a set of agents and a set of …
D Chakrabarty, C Swamy - Proceedings of the 5th conference on …, 2014 - dl.acm.org
In this paper, we study mechanism design problems in the ordinal setting wherein the preferences of agents are described by orderings over outcomes, as opposed to specific …
E McDermid, RW Irving - Journal of combinatorial optimization, 2011 - Springer
An instance of the popular matching problem (POP-M) consists of a set of applicants and a set of posts. Each applicant has a preference list that strictly ranks a subset of the posts. A …
H Aziz, G Csáji, Á Cseh - International Symposium on Algorithmic Game …, 2023 - Springer
We study deviations by a group of agents in the three main types of matching markets: the house allocation, the marriage, and the roommates models. For a given instance, we call a …
K Paluch - International Conference on Algorithms and …, 2013 - Springer
We consider capacitated rank-maximal matchings. Rank-maximal matchings have been considered before and are defined as follows. We are given a bipartite graph …
K Paluch - Theoretical Computer Science, 2014 - Elsevier
Suppose that each member of a set of agents has a preference list of a subset of houses, possibly involving ties, and each agent and house has their capacity denoting the maximum …