MAP Inference via Block-Coordinate Frank-Wolfe Algorithm

Paul Swoboda, Vladimir Kolmogorov; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 11146-11155

Abstract


We present a new proximal bundle method for Maximum-A-Posteriori (MAP) inference in structured energy minimization problems. The method optimizes a Lagrangean relaxation of the original energy minimization problem using a multi plane block-coordinate Frank-Wolfe method that takes advantage of the specific structure of the Lagrangean decomposition. We show empirically that our method outperforms state-of-the-art Lagrangean decomposition based algorithms on some challenging Markov Random Field, multi-label discrete tomography and graph matching problems.

Related Material


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[bibtex]
@InProceedings{Swoboda_2019_CVPR,
author = {Swoboda, Paul and Kolmogorov, Vladimir},
title = {MAP Inference via Block-Coordinate Frank-Wolfe Algorithm},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2019}
}