The spring quarter starts on April 3, 2023.
ECS 289G Advanced Deep Learning
Date: April 3-June 8, 2023
Time: T/R 10:30-11:50AM
Venue: CRUESS 107
Instructor: Jiawei Zhang
Office: Zoom Link to Join
Office Hours: T 12:10-13:10PM
Teaching Assistant: Xinghao Xiang
Office Hours: TBD
The course on Advanced Deep Learning focuses on selective areas of importance about deep learning. Deep learning has been one of the hottest topics in AI studies, and techniques developed in the research hold substantial impacts in many important applications. Selective topics will be covered in the Advanced Deep Learning.
No required textbook.
You are expected to have background knowledge in Data Structure, Algorithm, Discrete Mathematics. You will also need to be familiar with basic Linear Algebra, basic Statistics, and can master at least one programming language and have programming experiences.
The objective of this course is to familiarize students with the latest research topics related to deep learning. Course activities include 1) paper reading and paper review; 2) paper presentation and discussion; and 3) research oriented course paper writing.
In-class presentation: 30% . Powerpoint presentation needs to be submitted on the day of the presentation, before 11:59PM (midnight) of your presentation day. Copying existing presentation from the web is regarded as plagiarism.
Course participation and QA: 20% . A summary/review of each in-class discussion paper needs to be submitted before each class starts. During the class, presenter and audiences can have Q&A with the pre-prepared questions in the review report.
Course paper: 50% . An original work on deep learning. Not recycled published/submitted/on-going work with another faculties or classes.