# MAP inference via Block-Coordinate Frank-Wolfe Algorithm

arXiv: https://arxiv.org/abs/1806.05049 · HTML: https://mlsanity.com/paper/1806.05049/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Jun 2018.

## Built on by (most cited first, 2 of 2)

- [Structured Prediction Problem Archive](https://mlsanity.com/paper/2202.03574/) (2022)
- [Fast block-coordinate Frank-Wolfe algorithm for semi-relaxed optimal transport](https://mlsanity.com/paper/2103.05857/) (2021)

## Abstract (arXiv)

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.