Ene, Alina, Nguyen, Huy and Végh, László A. 
ORCID: 0000-0003-1152-200X
(2017)
Decomposable submodular function minimization: discrete and continuous.
In: Guyon, I., Luxburg, U. V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S. and Garnett, R., (eds.)
Advances in Neural Information Processing Systems 30 (NIPS 2017) pre-proceedings.
Neural Information Processing Systems Foundation, Long Beach, USA.
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
| Item Type: | Book Section |
|---|---|
| Official URL: | https://papers.nips.cc/book/advances-in-neural-inf... |
| Additional Information: | © 2017 Neural Information Processing Systems Foundation |
| Divisions: | Mathematics |
| Subjects: | Q Science > QA Mathematics |
| Date Deposited: | 08 Jan 2018 16:24 |
| Last Modified: | 10 Apr 2024 00:33 |
| URI: | http://eprints.lse.ac.uk/id/eprint/86395 |
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