LGS obtains the student-optimal matching by performing interviews. When all colleges have identical partial preferences (i.e., the Identical Equivalence Class condition (IEC) is satisfied), LGS minimizes the number of interviews among all the policies that obtain the student-optimal matching.
Oct 27, 2021 · The Lazy Gale-Shapley policy (LGS) [23] is an extension of the Gale-Shapley algorithm (GS) [8] for one-to-one matching with partial information.
This paper extends LGS to a significantly more practical many-to-one setting, in which a college can accept multiple students up to its quota. Our extended LGS ...
In practice, however, each agent initially has only partial information and needs to refine it by costly actions (interviews). For one-to-one matching with ...
For one-to-one matching with partial information, the student-proposing Lazy Gale-Shapley policy (LGS) minimizes the number of interviews when colleges have ...
This paper extends LGS to a significantly more practical many-to-one setting, in which a college can accept multiple students up to its quota. Our extended LGS ...
Dive into the research topics of 'Lazy Gale-Shapley for Many-to-One Matching with Partial Information'. Together they form a unique fingerprint. Sort by; Weight ...
This paper extends LGS to a significantly more practical many-to-one setting, in which a college can accept multiple students up to its quota. Our extended LGS ...
Lazy Gale-Shapley for Many-to-One Matching with Partial Information. Proceedings of the 7th International Conference on Algorithmic Decision Theory (ADT).
Lazy Gale-Shapley for Many-to-One Matching with Partial Information. Taiki Todo Ryoji Wada Kentaro Yahiro Makoto Yokoo. Published in: ADT (2021). Keyphrases.