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COMP 5970/6970: Federated and Collaborative Machine Learning
Instructor: Jiaqi Wang
Lecture: MWF 14:00-14:50
Office Hours: M 14:50-15:50
TA: Darryl Cherian Jacob
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Course Overview
This course explores advanced techniques in federated learning, collaborative machine learning, and multi-agent systems that enable decentralized model training across distributed data sources. Also, we will examine recent developments in deploying large language models (LLMs) and foundation models in federated and collaborative settings, with a focus on real-world applications in computer vision, Internet of Things (IoT), and healthcare. Students will engage with state-of-the-art literature, identify open research problems, and critically analyze recent advances shaping the future of collaborative intelligence.
Schedule
The schedule is tentative and subject to change. Please see the table below for the latest updates.
| Date |
Topics |
Notes |
Due |
| 08/18 (M) |
Course Overview |
Syllabus and logistics |
| 08/20 (W) |
Introduction and Background: Part I |
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| 08/22 (F) |
Introduction and Background: Part II |
Last day to add course |
| 08/25 (M) |
Foundation of Federated Learning |
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| 08/27 (W) |
Data Heterogeneity in Federated Learning |
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| 08/29 (F) |
How to Read Papers |
1st Batch Paper Release |
| 09/01 (M) |
No Class |
Labor Day |
| 09/03 (W) |
Model Heterogeneity in Federated Learning |
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| 09/05 (F) |
How to Conduct Professional Presentations |
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| 09/08 (M) |
Federated semi-supervised learning |
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| 09/10 (W) |
Federated Learning Meets Large Models |
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| 09/12 (F) |
Federated Learning Implementation |
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| 09/15 (M) |
Federated Learning in Healthcare |
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| 09/17 (W) |
Paper Presentation |
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Slides due by 09/15 |
| 09/19 (F) |
Paper Presentation |
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| 09/22 (M) |
Paper Presentation |
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| 09/24 (W) |
Paper Presentation |
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| 09/26 (F) |
Paper Presentation |
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| 09/29 (M) |
Paper Presentation |
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| 10/01 (W) |
Introduction of LLMs |
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| 10/03 (F) |
Mid Wrap-up |
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Bonus: idea submission due by 10/02 |
| 10/06 (M) |
Multi-agent Basis |
2nd batch paper release |
| 10/08 (W) |
Course Project Introduction |
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1st Batch Paper Release
| 10/10 (F) |
No Class |
Fall break |
| 10/13 (M) |
Project Proposal Introduction |
How to conduct professional writing |
| 10/15 (W) |
How to Write a Research Paper |
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| 10/17 (F) |
No class: Prepare slides at home |
Conference Travel |
| 10/20 (M) |
Project Proposal Pitch (online) |
Conference travel |
Slides due by 10/19 |
| 10/22 (W) |
Project Proposal Pitch (online) |
Conference travel |
| 10/24 (F) |
Project Proposal Pitch (online) |
Conference travel |
| 10/27 (M) |
Project Proposal Writing Office Hours |
You can feel free to stop by to get feedback. |
| 10/29 (W) |
Multi-agent Advance: Part I |
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| 10/31 (F) |
Guest Speaker: Dr.Yu Zhang |
Assistant Professor, Texas A&M University |
Project Proposal due by 10/31 |
| 11/03 (M) |
Multi-agent Advance: Part II |
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| 11/05 (W) |
Multi-agent: Future Directions |
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| 11/07 (F) |
Paper Presentation |
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Slides due by 11/06 |
| 11/10 (M) |
Paper Presentation |
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| 11/12 (W) |
Paper Presentation |
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| 11/14 (F) |
Paper Presentation |
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| 11/17 (M) |
Final Wrap-up |
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Bonus: idea submission due by 11/16 |
| 11/19 (W) |
Guest Lecture (TBD) |
Invite guests from industry or academia |
| 11/21 (F) |
Project Office Hours |
Provide help for your project |
| 11/24 (M) |
No Class |
Thanksgiving break |
| 11/26 (W) |
No Class |
Thanksgiving break |
| 11/28 (F) |
No Class |
Thanksgiving break |
| 12/01 (M) |
Final Presentation |
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Slides due by 11/30 |
| 12/03 (W) |
Final Presentation |
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| 12/05 (F) |
Final Presentation |
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| 12/08 (M) |
Final Presentation |
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| 12/10 (W) |
Final week: no exams or classes |
Writing final paper |
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| 12/12 (F) |
Final week: no exams or classes |
Writing final paper |
Final paper due by 12/12 |
Grading
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Paper Presentation and Slides (20%):
- There are two paper presentations. Each student is required to present one paper in each round.
- Each slides and each presentation count towards 5% of the final grade.
- Online students need to share the link of the video recording for the presentation.
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Project Proposal (30%)
- Project proposal writing report counts towards 10% of the final grade.
- Project proposal pitch presentation counts towards 20% of the final grade.
- Online students need to share the link of the video recording for the presentation.
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Final Project (50%)
- Project proposal writing report counts towards 20% of the final grade.
- Project proposal pitch presentation counts towards 30% of the final grade.
- Online students need to share the link of the video recording for the presentation.
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Bonus
- Idea bonus: Each submission is 1-page of what you may think is interesting or any bold reseach ideas based on the lectures.
Each submission adds 5 points to the actural grade. We totally have 2 submission opportunities.
- Paper submission: You are encouraged to submit your project paper to
AI/ML/DM conferences.
The instructor will provide a comprehensive evaluation of the work before the final grading day.
The submission is required to be reviewed and approved by the instructor. The approved paper adds 10 points to the actural grade.
Please notice that the bar of the paper submission could be (much) higher than a course project.
- Course survey: The survey completion rate >80% leads to an additional 10% for everyone’s actual grades, i.e., your_final_grade = your_actual_grade * 110%
Late Policy
- Late assignments are generally not accepted. If you are unable to meet a deadline due to extenuating circumstances, you must notify the instructor as early as possible in advance.
- May be submitted late with a 25% penalty for every 12 hours late, up to 48 hours (2 days).
After 48 hours, no credit will be given for the submission.
Academic Integrity
Auburn University is dedicated to honesty and strong moral behavior in academics. Cheating and plagiarism are expressly prohibited by the Auburn University Academic Honesty Code.
Students who attend Auburn are expected to attain high competency and deep understanding in their areas of study. While developing skills and knowledge, it is essential that Auburn students commit themselves to core principles and behaviors consistent with academic and personal integrity:
- Honesty: Upholding trust and honesty by doing your own academic work and not cheating.
- Fairness: Following correct academic procedures and practices as stated in course guidelines and as defined by Auburn University.
- Respect: Growing as a student by facing academic challenges and interacting productively with instructors.
- Responsibility: Being accountable for and accepting responsibility for class assignments and personal academic development.
More details can be found in the
Auburn University Academic Honesty Code.
Instructor's extra notes: we have
zero tolerance for academic dishonesty. If you are cheating in any forms (slides, presentations, writing etc.),
you will receive a zero for the assignment and may fail the course. I hope we can trust and respect each other.
Accommodation Policy
Our lectures strictly follow the
Auburn University policies on accommodations for students.
If you have a disability and require accommodations, please contact the Office of Accessibility at Auburn University. Also, please discuss your accommodations and needs with the instructor as early as possible before the course begins. I will work with you to ensure that accommodations are provided appropriately.
Syllabus and Grading Change Policy
The Instructor reserves the right to make changes to the syllabus and grading policy as necessary. Any changes will be communicated to students in a timely manner.