@inproceedings{7468,
  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.},
  author       = {Swoboda, Paul and Kolmogorov, Vladimir},
  booktitle    = {Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition},
  isbn         = {9781728132938},
  issn         = {10636919},
  location     = {Long Beach, CA, United States},
  publisher    = {IEEE},
  title        = {{Map inference via block-coordinate Frank-Wolfe algorithm}},
  doi          = {10.1109/CVPR.2019.01140},
  volume       = {2019-June},
  year         = {2019},
}