TA4b: Theory of Deep Learning (Invited) |
Session Type: Oral |
Time: Tuesday, November 5, 10:15 - 11:55 |
Location: Heather |
Session Chairs: Richard Baraniuk, Rice University and Santiago Segarra, Rice University
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TA4b-1: A SPLINE THEORY OF DEEP NETWORKS |
Randall Balestriero; Rice University |
Richard Baraniuk; Rice University |
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TA4b-2: INFORMATION IN THE WEIGHTS AND EMERGENT PROPERTIES OF TRAINING DEEP NEURAL NETWORKS |
Alessandro Achille; University of California, Los Angeles |
Stefano Soatto; University of California, Los Angeles |
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TA4b-3: UNDERSTANDING GENERALIZATION IN NEURAL NETS VIA VISUALIZATION |
W Huang; University of Maryland |
Zeyad Emam; University of Maryland |
Micah Goldblum; University of Maryland |
Liam Fowl; University of Maryland |
Justin Terry; University of Maryland |
Tom Goldstein; University of Maryland |
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TA4b-4: ON EXACT COMPUTATION WITH AN INFINITELY WIDE NEURAL NET |
Sanjeev Arora; Princeton University |
Simon S. Du; Carnegie Mellon University |
Wei Hu; Princeton University |
Zhiyuan Li; Princeton University |
Ruslan Salakhutdinov; Carnegie Mellon University |
Ruosong Wang; Carnegie Mellon University |
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TA4b-5: DO IMAGENET CLASSIFIERS GENERALIZE TO IMAGENET? |
Benjamin Recht; University of California, Berkeley |
Rebecca Roelofs; University of California, Berkeley |
Ludwig Schmidt; University of California, Berkeley |
Vaishaal Shankar; University of California, Berkeley |
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