632 citations · 1.1k across the 9 of their papers we have counts for
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stat.ML2014★ 35 cited
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…
stat.ML2014★ 40 cited
Learning the Parameters of Determinantal Point Process Kernels
Raja Hafiz Affandi, Emily B. Fox, Ryan P. Adams +1
Determinantal point processes (DPPs) are well-suited for modeling repulsion and have proven useful in many applications where diversity is desired. While DPPs have many appealing p…