(Probably) Concave Graph Matching
Optimization and Control
2018-12-27 v3 Combinatorics
Abstract
In this paper we address the graph matching problem. Following the recent works of \cite{zaslavskiy2009path,Vestner2017} we analyze and generalize the idea of concave relaxations. We introduce the concepts of conditionally concave and probably conditionally concave energies on polytopes and show that they encapsulate many instances of the graph matching problem, including matching Euclidean graphs and graphs on surfaces. We further prove that local minima of probably conditionally concave energies on general matching polytopes (e.g., doubly stochastic) are with high probability extreme points of the matching polytope (e.g., permutations).
Cite
@article{arxiv.1807.09722,
title = {(Probably) Concave Graph Matching},
author = {Haggai Maron and Yaron Lipman},
journal= {arXiv preprint arXiv:1807.09722},
year = {2018}
}
Comments
Neural Information Processing Systems (NeurIPS) 2018