NeurIPS 2017spotlight32 citations
Decomposable Submodular Function Minimization: Discrete and Continuous
Alina Ene, Huy Nguyen, László A. Végh
Abstract
This paper investigates connections between discrete and continuous approaches for decomposable submodular function minimization. We provide improved running time estimates for the state-of-the-art continuous algorithms for the problem using combinatorial arguments. We also provide a systematic experimental comparison of the two types of methods, based on a clear distinction between level-0 and level-1 algorithms.
BibTeX
@inproceedings{NIPS2017_c1fea270,
author = {Ene, Alina and Nguyen, Huy and V\'{e}gh, L\'{a}szl\'{o} A.},
booktitle = {Advances in Neural Information Processing Systems},
editor = {I. Guyon and U. Von Luxburg and S. Bengio and H. Wallach and R. Fergus and S. Vishwanathan and R. Garnett},
pages = {},
publisher = {Curran Associates, Inc.},
title = {Decomposable Submodular Function Minimization: Discrete and Continuous},
url = {https://proceedings.neurips.cc/paper_files/paper/2017/file/c1fea270c48e8079d8ddf7d06d26ab52-Paper.pdf},
volume = {30},
year = {2017}
}