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作者:N Tishby2015被引用次数:735 — Abstract: Deep Neural Networks (DNNs) are analyzed via the theoretical framework of the information bottleneck (IB) principle.
作者:N Tishby2015被引用次数:738 — Abstract—Deep Neural Networks (DNNs) are analyzed via the theoretical framework of the information bottleneck (IB) principle. We first show that any DNN can ...
5 页·352 KB
作者:AM Saxe2018被引用次数:262 — In this view, deep learning is a question of representation learning: each layer of a deep neural network can be seen as a set of summary statistics which ...

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2018年7月28日 — 上次读了《Deep Learning under Privileged Information Using Heteroscedastic Dropout》这篇文章,里面提到了信息瓶颈(Information Bottleneck)这个 ...
2017年9月21日 — Tishby argues that deep neural networks learn according to a procedure called the “information bottleneck,” which he and two collaborators ...
(原始内容存档 (PDF)于2017-08-29). ^ Naftali Tishby, Noga Zaslavsky. Deep Learning and the Information Bottleneck Principle. 2015.
Information theory of deep learning — [edit]. Theory of Information Bottleneck is recently used to study Deep Neural Networks (DNN). Consider ...
2015年3月9日 — The information bottleneck theory of deep learning proposes that neural networks achieve good generalization by compressing their ...
作者:BC Geiger2020 — Keywords: information bottleneck; deep learning; neural networks ... frameworks inspired by the IB principle, but that depart from them in a ...
作者:A Elad被引用次数:11 — The information bottleneck (IB) has been suggested as a fundamental principle governing performance in deep neural nets (DNNs). This idea sparked research.
5 页·384 KB

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