Diversity maximization aims to select a diverse and representative subse...
Graph summarization via node grouping is a popular method to build conci...
Diversity maximization is a fundamental problem with wide applications i...
Recommender systems typically suggest to users content similar to what t...
Bayesian networks are popular probabilistic models that capture the
cond...
Machine unlearning is the task of updating machine learning (ML) models ...
The node classification problem is to infer unknown node labels in a gra...
We study the problem of extracting a small subset of representative item...
We study the problem of selecting the top-k candidates from a pool of
ap...
Extracting a small subset of representative tuples from a large database...
In this paper, we study university admissions under a centralized system...
We consider the problem of designing affirmative action policies for
sel...
We consider a setting where a Bayesian network has been built over a
rel...