PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Consistent structured estimation for weighted bipartite matching
James Petterson, Tiberio Caetano and Julian McAuley
In: NIPS Workshop on Algebraic and Combinatorial Methods in Machine Learning, 12-13 Dec 2008, Whistler, Canada.

Abstract

Given a weighted bipartite graph, the assignment problem consists of finding the heaviest perfect match. This is a classical problem in combinatorial optimization, which is solvable exactly and efficiently by standard methods such as the Hungarian algorithm, and is widely applicable in real-world scenarios. We give an exponential family model for the assignment problem. Edge weights are obtained from a suitable composition of edge features and a parameter vector, which is learned so as to maximize the likelihood of a sample consisting of training graphs and their labeled matches. The resulting consistent estimator contrasts with existing max-margin structured estimators, which are inconsistent for this problem.

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EPrint Type:Conference or Workshop Item (Speech)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
ID Code:5545
Deposited By:Julian McAuley
Deposited On:25 February 2010