Optimization Methods for Deep Learning


Course Outline

Deep learning involves a difficult non-convex optimization problem. The goal of this course is to study the implementation of optimization methods for deep learning. We will run this course in the following formats: For potential students: you want to make sure that you are interested in optimization for deep learning.

We will heavily use the software simpleNN

Among the various types of networks, we will pay more attention to CNN.

You will get hands-on experiences in implementing a deep learning code


Slides and recordings

This section (and slides) will be continuously updated.

Projects


Exams

No exam

Grading

100% Projects.

Issues related to COVID-19


Acknowledgements: the following people have greatly helped to prepare materials for this course (including creating the software used for the course and trying some projects). Chien-Chih Wang, Kent Loong Tan, Pin-Yen Lin, Cheng-Hung Liu (former and current members in my group), Pengrui Quan (UCLA), and Leonardo Galli (University of Florence)

Last modified: