We can learn a lot about Why Deep Learning Works by studying the properties of the layer weight matrices of pre-trained neural networks. And, hopefully,
Author: Charles H Martin, PhD
Machine Learning Enthusiast and Consultant
Power Laws in Deep Learning 2: Universality
Power Law Distributions in Deep Learning In a previous post, we saw that the Fully Connected (FC) layers of the most common pre-trained Deep Learning
Power Laws in Deep Learning
Why Does Deep Learning Work ? If we could get a better handle on this, we could solve some very hard problems in Deep Learning. A
Self-Regularization in Deep Neural Networks: a preview
Why Deep Learning Works: Self Regularization in DNNs An early talk describing details in this paper Implicit Self-Regularization in Deep Neural Networks: Evidence from Random
Rethinking–or Remembering–Generalization in Neural Networks
Rethinking Generalization: the Google paper Last year, ICLR 2017, a very interesting paper came out of Google claiming that Understanding Deep Learning Requires Rethinking Generalization
Capsule Networks: A video presentation
Please enjoy my video presentation on Geoff Hinton’s Capsule Networks. What they are, why they are important, and how they are implemented (in Keras) …
