Program

 

Time
 
Wednesday, Nov. 29
 
Thursday, Nov. 30
 
Friday, Dec. 1
 
08:00-09:00 Registration and Coffee
Main Building TU Berlin
- -
09:00-11:00 Klaus-Robert Müller
Explaining nonlinear learning machines and applications
Philipp Grohs
Approximation Theory of Neural Networks
Lars Ruthotto
An Optimal Control Framework for Efficient Training of Deep Neural Networks
11:00-11:30 Coffee Break Coffee Break Coffee Break
11:30-13:30 René Vidal
Global Optimality in Matrix Factorization and Deep Learning
Michael Elad
From Shallow to Deep Sparsity with Convolutional Networks
Julien Mairal
Towards deep kernel machines
13:30-14:30  
Lunch Break
 
Lunch Break Lunch Break
14:30-16:30 Helmut Bölcskei
Harmonic analysis of deep convolutional neural networks
Gitta Kutyniok
Memory-optimal Deep Neural Networks
Vignesh Srinivasan
Introduction to TensorFlow II
16:30-17:00 Coffee Break Coffee Break -
17:00-19:00 Vignesh Srinivasan
Introduction to TensorFlow I
Wojciech Samek
Towards explainable Deep Learning
20:00 - social event
visit of a christmas market



List of Abstracts