Learning determinantal point processes by corrective negative sampling

Determinantal Point Processes (DPPs) have attracted significant interest from the machine-learning community due to their ability to elegantly and tractably model the delicate balance between quality and diversity of sets. DPPs are commonly learned from data using maximum likelihood estimation (MLE)...

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Bibliographic Details
Main Authors: Mariet, Zelda (Author), Gartrell, Mike (Author), Sra, Suvrit (Author)
Other Authors: Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory (Contributor)
Format: Article
Language:English
Published: MLResearch Press, 2021-04-08T15:13:46Z.
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