Constrained Submodular Maximization: Beyond 1/e

In this work, we present a new algorithm for maximizing a non-monotone submodular function subject to a general constraint. Our algorithm finds an approximate fractional solution for maximizing the multilinear extension of the function over a down-closed polytope. The approximation guarantee is 0. 372 and it is the first improvement over the 1/e approximation achieved by the unified Continuous Greedy algorithm [Feldman et al. , FOCS 2011].

Authors

• Alina Ene
• Huy L. Nguyen 0001

Keywords

• Optimized production technology
• Approximation algorithms
• Greedy algorithms
• Algorithm design and analysis
• Standards
• Computer science
• Electronic mail
• Submodular Maximization
• Polytope
• Fractional Solution
• Right-hand Side
• Analytical Solutions
• Remainder Of This Section
• Side Of Inequality
• Gain Margin
• Box Constraints
• submodular functions
• maximization