Learning Determinantal Point Processes in Sublinear Time

@inproceedings{Dupuy2016LearningDP,
  title={Learning Determinantal Point Processes in Sublinear Time},
  author={Christophe Dupuy and Francis R. Bach},
  booktitle={AISTATS},
  year={2016}
}
We propose a new class of determinantal point processes (DPPs) which can be manipulated for inference and parameter learning in potentially sublinear time in the number of items. This class, based on a specific low-rank factorization of the marginal kernel, is particularly suited to a subclass of continuous DPPs and DPPs defined on exponentially many items. We apply this new class to modelling text documents as sampling a DPP of sentences, and propose a conditional maximum likelihood… CONTINUE READING
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