Technical Program

TN2: Mathematics of Deep Learning

Session Type: Lecture
Time: Tuesday, December 17, 16:00 - 17:20
Location: Salle Route du Rhum
Session Chairs: René Vidal, Johns Hopkins University and Jeremias Sulam, John Hopkins University
 
TN2.1: GEOMETRIC DEEP LEARNING: APPROACHES AND APPLICATIONS
Federico Monti, Twitter, United States
 
TN2.2: THE COMPLEXITY OF LEARNING DEEPLY-SPARSE SIGNAL REPRESENTATIONS
Demba Ba, Harvard University, United States
 
TN2.3: RATE-DISTORTION EXPLANATION (RDE): A THEORETICAL FRAMEWORK FOR INTERPRETING NEURAL NETWORK DECISIONS
Jan Macdonald, Stephan Wäldchen, Sascha Hauch, Gitta Kutyniok, TU Berlin, Germany
 
TN2.4: GEOMETRIC APPROACH TO MATRIX COMPLETION
Sanketh Vedula, Amit Boyarski, Alex Bronstein, Technion, Israel