Motivated by practical generalizations of the classic k-median and k-means objectives, such
as clustering with size constraints, fair clustering, and Wasserstein barycenter, we introduce …

Streaming submodular maximization is a natural model for the task of selecting a
representative subset from a large-scale dataset. If datapoints have sensitive attributes such …

The clustering problem of big data in the era of artificial intelligence has been widely
studied. Because of the huge amount of data, distributed algorithms are often used to deal …

The $ k $-center problem is a classical clustering problem in which one is asked to find a
partitioning of a point set $ P $ into $ k $ clusters such that the maximum radius of any …

The k-center problem is a classical clustering problem in which one is asked to find a
partitioning of a point set P into k clusters such that the maximum radius of any cluster is …

The goal of recommender systems is to provide to users suggestions that match their
interests, with the eventual goal of increasing their satisfaction, as measured by the number …