Information Theoretic Interpretation of Deep learning
Machine Learning
2018-03-23 v2 Artificial Intelligence
Information Theory
math.IT
Machine Learning
Abstract
We interpret part of the experimental results of Shwartz-Ziv and Tishby [2017]. Inspired by these results, we established a conjecture of the dynamics of the machinary of deep neural network. This conjecture can be used to explain the counterpart result by Saxe et al. [2018].
Cite
@article{arxiv.1803.07980,
title = {Information Theoretic Interpretation of Deep learning},
author = {Tianchen Zhao},
journal= {arXiv preprint arXiv:1803.07980},
year = {2018}
}
Comments
17 pages, 7 figures