632 citations · 1.1k across the 9 of their papers we have counts for
3 papers · 1 filter
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…
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…
Controlling Complexity in Part-of-Speech Induction
João V. Graça, Kuzman Ganchev, Luisa Coheur +2
We consider the problem of fully unsupervised learning of grammatical (part-of-speech) categories from unlabeled text. The standard maximum-likelihood hidden Markov model for this…