Fast Maximization of Non-Submodular, Monotonic Functions on the Integer Lattice
May 17, 2018 Β· Declared Dead Β· π International Conference on Machine Learning
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Authors
Alan Kuhnle, J. David Smith, Victoria G. Crawford, My T. Thai
arXiv ID
1805.06990
Category
cs.DS: Data Structures & Algorithms
Citations
44
Venue
International Conference on Machine Learning
Last Checked
3 months ago
Abstract
The optimization of submodular functions on the integer lattice has received much attention recently, but the objective functions of many applications are non-submodular. We provide two approximation algorithms for maximizing a non-submodular function on the integer lattice subject to a cardinality constraint; these are the first algorithms for this purpose that have polynomial query complexity. We propose a general framework for influence maximization on the integer lattice that generalizes prior works on this topic, and we demonstrate the efficiency of our algorithms in this context.
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