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Title: A Nearly-linear Time Algorithm for Submodular Maximization with a Knapsack Constraint
We consider the problem of maximizing a monotone submodular function subject to a knapsack constraint. Our main contribution is an algorithm that achieves a nearly-optimal, $1 - 1/e - \epsilon$ approximation, using $(1/\epsilon)^{O(1/\epsilon^4)} n \log^2{n}$ function evaluations and arithmetic operations. Our algorithm is impractical but theoretically interesting, since it overcomes a fundamental running time bottleneck of the multilinear extension relaxation framework. This is the main approach for obtaining nearly-optimal approximation guarantees for important classes of constraints but it leads to $\Omega(n^2)$ running times, since evaluating the multilinear extension is expensive. Our algorithm maintains a fractional solution with only a constant number of entries that are strictly fractional, which allows us to overcome this obstacle.  more » « less
Award ID(s):
1718342 1750333
NSF-PAR ID:
10105031
Author(s) / Creator(s):
;
Date Published:
Journal Name:
International Colloquium on Automata, Languages, and Programming
Volume:
132
Page Range / eLocation ID:
53:1--53:12
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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