Learning Signed Determinantal Point Processes through the Principal Minor Assignment Problem

Victor-Emmanuel Brunel

Neural Information Processing Systems 

Sampling and learning these symmetric DPP's is pretty well understood. In this work, we consider a new class of DPP's, which we call signed DPP's, where we break the symmetry and allow attractive behaviors.

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