Research map / Learning theory and algorithms / Submodular and game algorithms
Non-monotone Submodular Optimization: $p$-Matchoid Constraints and Fully Dynamic Setting
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Studies non-monotone submodular maximization under p-matchoid constraints in the fully dynamic setting with insertions and deletions.
Problem
Maximizing a non-monotone submodular function subject to a p-matchoid constraint when the ground set undergoes a sequence of element insertions and deletions.
Approach
Dynamic algorithms for non-monotone submodular maximization under p-matchoid constraints, extending prior work on this problem to the fully dynamic setting (details not available beyond the abstract).
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