Jul 24, 2023
Sprecher:in · 0 Follower:innen
Sprecher:in · 0 Follower:innen
Sprecher:in · 0 Follower:innen
Sprecher:in · 0 Follower:innen
Sprecher:in · 0 Follower:innen
Sprecher:in · 0 Follower:innen
Maximizing a monotone submodular function under cardinality constraint k is a core problem in machine learning and database with many basic applications, including video and data summarization, recommendation systems, feature extraction, exemplar clustering, and coverage problems. We study this classic problem in the fully dynamic model where a stream of inserts and deletes of elements of an underlying ground set is given and the goal is to maintain an approximate solution using a fast update time.Very recently, at NeurIPS'20, Lattanzi, Mitrovic, Norouzi-Fard, Tarnawski, Zadimoghaddam claimed to obtain a dynamic algorithm for this problem in the fully dynamic setting using a very complicated algorithm with poly(log(n),log(k),ϵ^-1) update time.However, as we explain in this paper, their analysis has serious gaps that might not be fixable. Having a dynamic algorithm for the problem with polylogarithmic update time is even more important in light of a recent result by Chen and Peng at STOC'22 who show a lower bound for submodular maximization in the dynamic model. In particular, their result states that any randomized algorithm that achieves an approximation ratio of 1/2+ϵ for dynamic submodular maximization under cardinality constraint k requires amortized query time n^Ω̃(ϵ)/k^3. In this paper, we develop a much simpler and a correct algorithm than that proposed by Lattanzi et al. which maintains an (1/2-ϵ)-approximate solution for submodular maximization under cardinality constraint k using a polylogarithmic amortized update time.Maximizing a monotone submodular function under cardinality constraint k is a core problem in machine learning and database with many basic applications, including video and data summarization, recommendation systems, feature extraction, exemplar clustering, and coverage problems. We study this classic problem in the fully dynamic model where a stream of inserts and deletes of elements of an underlying ground set is given and the goal is to maintain an approximate solution using a fast update ti…
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