Normalized-cut graph partitioning aims to divide the set of nodes in a g...
Diversity maximization aims to select a diverse and representative subse...
This paper investigates a new yet challenging problem called Reverse
k-M...
A great variety of complex systems, from user interactions in communicat...
Graph summarization via node grouping is a popular method to build conci...
Submodular function maximization is central in numerous data science
app...
Finding a happiness maximizing set (HMS) from a database, i.e., selectin...
Diversity maximization is a fundamental problem with wide applications i...
Despite its benefits for children's skill development and parent-child
b...
Recommender systems typically suggest to users content similar to what t...
Many graph-based machine learning models are known to be vulnerable to
a...
We study the problem of extracting a small subset of representative item...
A great variety of complex systems ranging from user interactions in
com...
Extracting a small subset of representative tuples from a large database...
Selecting a small set of representatives from a large database is import...
Coresets are important tools to generate concise summaries of massive
da...
Massive volumes of data continuously generated on social platforms have
...