Trustworthy Machine Learning

Semester: Winter 2024/2025

Added: Oct 16, 2024

Winter 2024/2025

Instructor: Adam Dziedzic

Contact: adam.dziedzic@cispa.de

Lectures: Wednesdays 14:00 - 16:00, CISPA building (Stuhlsatzenhaus 5, Saarbrücken)

CMS

Description

Deploying machine learning in real-world systems necessitates methods to ensure trustworthy AI. This course explores research at the intersection of machine learning, privacy, and security. This course provides a comprehensive overview of techniques to build robust and trustworthy machine learning models, focusing on neural networks. We will examine seminal work on privacy-preserving machine learning methods. Our primary focus will be on Large Language Models (LLMs) and Diffusion Models (DMs). Throughout the course, we will discuss outstanding challenges and future research directions to make machine learning more robust, private, and trustworthy.

Class structure: In every class, we will discuss two papers. At the beginning of the semester, students will be assigned roles that will rotate every week. There are three roles:

  • The Presenters: Two students. Each of them presents a paper and takes the lead in answering the questions posed by the Questioners.

  • The Questioners: This group is responsible for preparing a list of 4–5 questions about the papers to be discussed in class. For a given week, The Questioners must prepare their questions during the preceding week, and send them to the rest of the class by 5 pm Monday. This means that the Questioners must read the papers for their assigned week several days in advance of the actual discussion sessions. We suggest aiming to read the papers by the end of the day on Sunday, to allow at least one day to discuss possible questions.

  • The Observers: This group will take notes on a shared document during a discussion. These notes are not meant to be a transcription of what is being said in the discussion; they should capture the major take-away points of the discussion, as well as any issues. The Observers should also search for additional resources or answers to unresolved questions.

These roles do not preclude anyone in the class from participating in the discussion. A member of The Observers can jump in when a question is posed, and a presenter can pose a new question on the fly.

Course Staff