Why Deep Learning Works: Self Regularization in DNNs Presented at UC Berkeley / NERSC Jun 8, 2018 Empirical results, using the machinery of Random Matrix
Author: Charles H Martin, PhD
Machine Learning Enthusiast and Consultant
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) …
Free Energies and Variational Inference
My Labor Day Holiday Blog: for those on email, I will add updates, answer questions, and make corrections over the next couple weeks. Thanks for
What is Free Energy: Hinton, Helmholtz, and Legendre
Hinton introduced Free Energies in his 1994 paper, Autoencoders, minimum description length, and Helmholtz Free Energy This paper, along with his wake-sleep algorithm, set the foundations
Interview with a Data Scientist
It’s always fun to be interviewed. Check out my recent chat with Max Mautner, the Accidental Engineer http://theaccidentalengineer.com/charles-martin-principal-consultant-calculation-consulting/
