Lecture Details
Days: Mondays, WednesdaysDuration: 10:30 AM - 11:45 AM (Jan 08 - Apr 26)
Lecture Hall: SHESC 340 (Tempe)
Submissions: Canvas
Syllabus: Course Syllabus
Live Lecture: Zoom Link provided in Canvas
Contact info: atricham@asu...
Description
In this course, we will explore the pivotal role of deep learning across various application domains, delving into its rapid advancements. However, our focus extends beyond mere accuracy on isolated datasets, particularly when deploying deep learning in real-world scenarios, especially those with high stakes. Taking a pragmatic perspective, we will examine the sociotechnical challenges that impede the seamless deployment of deep learning techniques in critical applications. Our emphasis lies in identifying and addressing these challenges to facilitate the effective integration of deep learning solutions. Drawing examples from diverse fields like autonomous driving, robotics, and healthcare, we aim to equip participants with the knowledge and strategies needed to navigate the complexities of deploying deep learning in high-stakes environments.Prerequisites :
It is highly recommended that students complete CSE 471: Introduction to AI or CSE 475: Foundations of Machine Learning in order to be successful in this course. We assume the students to have an understanding of deep learning and experience with one of the deep learning libraries such as pytorch.Course Schedule:
| WEEK | DATES | TOPICS | IMPORTANT DATES | NOTES |
|---|---|---|---|---|
| Week 1 | 01/08/2024 01/10/2024 |
Deep learning applications, models, and metrics | Week 1 Lecture | |
| Week 2 | 01/15/2024 01/17/2024 |
Martin Luther King Jr. Holiday Observed (No class) Debugging and deployment |
PyTorch Tutorials | |
| Week 3 | 01/22/2024 01/24/2024 |
Epistemic uncertainty | RAS-Tutorial Project Guidelines |
|
| Week 4 | 01/29/2024 01/31/2024 |
Model calibration | ||
| Week 5 | 02/05/2024 02/07/2024 |
Explainable AI techniques | ||
| Week 6 | 02/12/2024 02/14/2024 |
Considerations in Explainable AI | ||
| Week 7 | 02/19/2024 02/21/2024 |
Out-of-domain/distribution detection | ||
| Week 8 | 02/26/2024 02/28/2024 |
Project discussions | ||
| Week 9 | 03/04/2024 03/06/2024 |
Spring break (No class) | ||
| Week 10 | 03/11/2024 03/13/2024 |
Out-of-domain/distribution adaptation and generalization | ||
| Week 11 | 03/18/2024 03/20/2024 |
Adversarial attacks | ||
| Week 12 | 03/25/2024 03/27/2024 |
Bias and fairness: testing | ||
| Week 13 | 04/01/2024 04/03/2024 |
Bias and fairness: mitigation | ||
| Week 14 | 04/08/2024 04/10/2024 |
Privacy | ||
| Week 15 | 04/15/2024 04/17/2024 |
Law and Ethics | ||
| Week 16 | 04/22/2024 04/24/2024 |
Project discussions and evaluation |
Teaching Team :
(Instructor)
Office hours: Mon, 2:00 PM - 3:00 PM
Virtual: Meeting Link
(Teaching Assistant)
Office hours: Fri, 11:00 AM - 12:00 PM
Virtual: Meeting Link
(Instructional Assistant)
Office hours: Tue, 11:00 AM - 12:00 PM
Virtual: Meeting Link
(Grader)
Office hours: Ad-hoc (post grading)