My talk at ICSI-the International Computer Science Institute at UC Berkeley. ICSI is a leading independent, nonprofit center for research…
Don’t Peek part 2: Predictions without Test Data
This is a followup to a previous post: DON’T PEEK: DEEP LEARNING WITHOUT LOOKING … AT TEST DATA The idea…suppose…
Machine Learning and AI for the Lean Start Up
Machine Learning and AI for the Lean Start Up My recent talk at the French Tech Hub Startup Accelerator
Don’t Peek: Deep Learning without looking … at test data
What is the purpose of a theory ? To explain why something works. Sure. But what good is a theory…
Rank Collapse in Deep Learning
We can learn a lot about Why Deep Learning Works by studying the properties of the layer weight matrices of…
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…
Power Laws in Deep Learning
Why Does Deep Learning Work ? If we could get a better handle on this, we could solve some very…
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…
Rethinking–or Remembering–Generalization in Neural Networks
I just got back from ICLR 2019 and presented 2 posters, (and Michael gave a great talk!) at the Theoretical…
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…
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