Tuesday, April 10, 2018

Videos: The "Institute for Advanced Study - Princeton University Joint Symposium on 'The Mathematical Theory of Deep Neural Networks'"

Adam followed through with videos of the awesome workshop he co-organized last month:
Hi Igor,

Thanks for posting about our recent workshop --- The "Institute for Advanced Study - Princeton University Joint Symposium on 'The Mathematical Theory of Deep Neural Networks'" --- last month. I just wanted to follow up and let you know that for those that missed the live-stream, we have put videos of all the talks up online:

https://www.youtube.com/playlist?list=PLWQvhvMdDChyI5BdVbrthz5sIRTtqV6Jw

I hope you and your readers enjoy!

Cheers,

-Adam
----------------------------Adam CharlesPost-doctoral associatePrinceton Neuroscience InstitutePrinceton, NJ, 08550 

Thanks Adam ! Here are the videos:

9:10 Adam Charles: Introductory remarks


2
56:17 Sanjeev Arora: Why do deep nets generalize, that is, predict well on unseen data


3
59:34 Sebastian Musslick: Multitasking Capability vs Learning Efficiency in Neural Network Architectures


4
48:01 Joan Bruna: On the Optimization Landscape of Neural Networks


5
59:44 Andrew Saxe: A theory of deep learning dynamics: Insights from the linear case


6
51:13 Anna Gilbert: Toward Understanding the Invertibility of Convolutional Neural Networks


7
1:03:57 Nadav Cohen: On the Optimization of Deep Networks: Implicit Acceleration by Overparameterization


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