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Maximal Information Divergence from Statistical Models Defined by Neural Networks

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Publication:5410605
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DOI10.1007/978-3-642-40020-9_85zbMath1322.62060arXiv1303.0268OpenAlexW3105687236WikidataQ117383280 ScholiaQ117383280MaRDI QIDQ5410605

Guido Montúfar, Johannes Rauh, Nihat Ay

Publication date: 16 April 2014

Published in: Lecture Notes in Computer Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1303.0268


zbMATH Keywords

neural networkexponential familyKullback-Leibler divergencemulti-information


Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Statistical aspects of information-theoretic topics (62B10)


Related Items (3)

On limiting towards the boundaries of exponential families ⋮ Maximizing the Bregman divergence from a Bregman family ⋮ Factorized mutual information maximization




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