Tin giáo vụ

Scientific Seminar: Principled Frameworks for Designing Deep Learning Models: Efficiency, Expressivity, and Robustness

Chi tiết
Chuyên mục: English
Lượt xem: 78

"Probability - Statistics Seminar in January 2024" is going to be organized with a report by Dr. Nguyen Hung Minh Tan.

Dr. Tan Nguyen is currently an Assistant Professor of Mathematics (Presidential Young Professor) at the National University of Singapore (NUS). Before joining NUS, he was a postdoctoral scholar in the Department of Mathematics at the University of California, Los Angeles, working with Dr. Stanley J. Osher. He obtained his Ph.D. in Machine Learning from Rice University, where he was advised by Dr. Richard G. Baraniuk. Dr. Nguyen is an organizer of the 1st Workshop on Integration of Deep Neural Models and Differential Equations at ICLR 2020. He also had two awesome long internships with Amazon AI and NVIDIA Research. He is the recipient of the prestigious Computing Innovation Postdoctoral Fellowship (CIFellows) from the Computing Research Association (CRA), the NSF Graduate Research Fellowship, and the IGERT Neuroengineering Traineeship. He received his M.S. and B.S. in Electrical and Computer Engineering from Rice University in May 2018 and May 2014, respectively.

Undergraduate, Master and Ph.D. students and interested people are invited to participate the seminar.

    • Time:  09:30 a.m. Wendsday, June 26, 2024.
    • Location: Room E202B, Campus 1- University of Science (227 Nguyen Van Cu St., District 5, Ho Chi Minh City).

Title: Principled Frameworks for Designing Deep Learning Models: Efficiency, Expressivity, and Robustness

Summary of the report is as follows:

Designing deep learning models for practical applications, including those in computer vision, natural language processing, and mathematical modeling, is an art that often involves an expensive search over candidate architectures. In this talk, the speaker will introduce two novel optimization frameworks to facilitate the process of designing efficient and expressive deep learning models including the neural ordinary differential equations (Neural ODEs) and transformers.
 

Scan the QR code below or click on the link before June 25, 2024 to register to attend.

seminar_26.6_thay_Tan.png