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In this work, we study the problem of monotone non-submodular maximizationwith partition matroid constraint. Although a generalization of this problemhas been studied in literature, our work focuses on leveraging properties ofpartition matroid constraint to (1) propose algorithms with theoretical boundand efficient query complexity; and (2) provide better analysis on theoreticalperformance guarantee of some existing techniques. We further investigate thosealgorithms' performance in two applications: Boosting Influence Spread andVideo Summarization. Experiments show our algorithms return comparative resultsto the state-of-the-art algorithms while taking much fewer queries.

Efficient Algorithms for Monotone Non-Submodular Maximization with Partition Matroid Constraint