[Colloquium] Friday, January 31 @ 10:30 am ~ MLS Series ~ Tengyu Ma

[Annie Simmons]

University of Chicago and Toyota Technological Institute at Chicago
Machine Learning Seminar Series


Tengyu Ma, Assistant Professor
Standford

Friday, January 31, 10:30 - 11:30 am
JCL Rm 390
(Remote broadcast at TTIC Rm 526)

Title:
Designing Explicit Regularizers for Deep Models   

Abstract:
I will discuss some recent results on designing explicit regularizers to improve the generalization performances of deep neural networks. We derive data-dependent generalization bounds for deep neural networks. We empirically regularize the bounds and obtain improved generalization performance (in terms of the standard accuracy or the robust accuracy). I will also touch on recent results on applying these techniques to imbalanced datasets. 
 
Based on joint work with Colin Wei, Kaidi Cao, Adrien Gaidon, and Nikos Arechiga

Bio:
Tengyu Ma is an assistant professor of Computer Science and Statistics at Stanford University. He received his Ph.D. from Princeton University and B.E. from Tsinghua University. His research interests include topics in machine learning and algorithms, such as deep learning and its theory, non-convex optimization, deep reinforcement learning, representation learning, and high-dimensional statistics. He is a recipient of NIPS’16 best student paper award, COLT’18 best paper award, and ACM Doctoral Dissertation Award Honorable Mention.

Host: Nati Srebro





Annie Simmons
Project Assistant IV
Computer Science Department
John Crerar Library Building
5730 S. Ellis
Chicago, IL 60637 
773.834.2750
773.702.8487
simmons3 at cs.uchicago.edu

“The dream is free the hustle is sold separately"

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