Maximizing diversity over clustered data∗
Proceedings of the 2020 SIAM International Conference on Data Mining, pp. 649-657, 2020.
Maximum diversity aims at selecting a diverse set of high-quality objects from a collection, which is a fundamental problem and has a wide range of applications, e.g., in Web search. Diversity under a uniform or partition matroid constraint naturally describes useful cardinality or budget requirements, and admits simple approximation algo...More
Full Text (Upload PDF)
PPT (Upload PPT)