Work

A Dual Ascent Framework for Lagrangean Decomposition of Combinatorial Problems

Year: 2017

Type: conference-paper

Abstract: We propose a general dual ascent (message passing) framework for Lagrangean (dual) decomposition of combinatorial problems. Although methods of this type have shown their efficiency for a number of problems, so far there was no general algorithm applicable to multiple problem types. In this work, we propose such a general algorithm. It depends on several parameters, which can be used to optimize its performance in each particular setting. We demonstrate efficiency of our method on the graph matching and the multicut problems, where it outperforms state-of-the-art solvers including those based on the subgradient optimization and off-the-shelf linear programming solvers.

Source: IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings

DOI: 10.1109/cvpr.2017.526

Authors: Paul Swoboda, Jan Kuske, Bogdan Savchynskyy

Institutions: Institute of Science and Technology Austria, Heidelberg University, Technische Universität Dresden

Language: English

Topic: Complexity and Algorithms in Graphs

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: FP7 Ideas: European Research Council

Award: Discrete Optimization in Computer Vision: Theory and Practice