Determinantal Point Processes for Machine Learning

Determinantal Point Processes for Machine Learning
Author: Alex Kulesza
Publisher:
Total Pages: 176
Release: 2012
Genre: Computer algorithms
ISBN: 9781601986290


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This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine learning community.


Determinantal Point Processes for Machine Learning
Language: en
Pages: 176
Authors: Alex Kulesza
Categories: Computer algorithms
Type: BOOK - Published: 2012 - Publisher:

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This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine lear
Learning and Enforcing Diversity with Determinantal Point Processes
Language: en
Pages: 66
Authors: Zelda Elaine Mariet
Categories:
Type: BOOK - Published: 2016 - Publisher:

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As machine-learning techniques continue to require more data and become increasingly memory-heavy, being able to choose a subset of relevant, high-quality and d
Determinantal Point Processes for Machine Learning
Language: en
Pages: 178
Authors: Alex Kulesza
Categories: Computers
Type: BOOK - Published: 2012-11-29 - Publisher: Now Pub

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This monograph provides a comprehensible introduction to DPPs, focusing on the intuitions, algorithms, and extensions that are most relevant to the machine lear
“A” Combination of Machine Learning and Determinantal Point Processes in Wireless Networks
Language: en
Pages: 0
Authors: Gobika Balendra
Categories:
Type: BOOK - Published: 2021 - Publisher:

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Learning with Determinantal Point Processes
Language: en
Pages: 178
Authors: John A. Kulesza
Categories:
Type: BOOK - Published: 2012 - Publisher:

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