Kronecker Determinantal Point Processes

@inproceedings{Mariet2016KroneckerDP,
  title={Kronecker Determinantal Point Processes},
  author={Zelda Mariet and Suvrit Sra},
  booktitle={NIPS},
  year={2016}
}
Determinantal Point Processes (DPPs) are probabilistic models over all subsets a ground set of N items. They have recently gained prominence in several applications that rely on “diverse” subsets. However, their applicability to large problems is still limited due to theO(N) complexity of core tasks such as sampling and learning. We enable efficient sampling and learning for DPPs by introducing KRONDPP, a DPP model whose kernel matrix decomposes as a tensor product of multiple smaller kernel… CONTINUE READING
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