Title
Decomposable Submodular Function Minimization: Discrete and Continuous.
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.
Year
Venue
DocType
2017
ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 30 (NIPS 2017)
Conference
Volume
ISSN
Citations 
30
1049-5258
3
PageRank 
References 
Authors
0.39
14
3
Name
Order
Citations
PageRank
Alina Ene140925.47
Huy L. Nguyen237632.33
László A. Végh37417.96