106 citations · 167 across the 4 of their papers we have counts for
4 papers
Diversifying Sparsity Using Variational Determinantal Point Processes
Nematollah Kayhan Batmanghelich, Gerald Quon, Alex Kulesza +3
We propose a novel diverse feature selection method based on determinantal point processes (DPPs). Our model enables one to flexibly define diversity based on the covariance of fea…
Expectation-Maximization for Learning Determinantal Point Processes
Jennifer Gillenwater, Alex Kulesza, Emily Fox +1
A determinantal point process (DPP) is a probabilistic model of set diversity compactly parameterized by a positive semi-definite kernel matrix. To fit a DPP to a given task, we wo…
Social Collaborative Retrieval
Ko-Jen Hsiao, Alex Kulesza, Alfred Hero
Socially-based recommendation systems have recently attracted significant interest, and a number of studies have shown that social information can dramatically improve a system's p…
Learning Determinantal Point Processes
Alex Kulesza, Ben Taskar
Determinantal point processes (DPPs), which arise in random matrix theory and quantum physics, are natural models for subset selection problems where diversity is preferred. Among…