Hot Topics in Explainable Machine Learning and Artificial Intelligence (XAI)

Overview

SemesterSummer 2023
Course typeBlock Seminar
LecturerJun.-Prof. Dr. Wressnegger
AudienceInformatik Master & Bachelor
Credits4 ECTS
Room148, Building 50.34
LanguageEnglish
LinkTBA
RegistrationTBA

Description

This seminar is concerned with explainable machine learning in computer security. Learning-based systems often are difficult to interpret, and their decisions are opaque to practitioners. This lack of transparency is a considerable problem in computer security, as black-box learning systems are hard to audit and protect from attacks.

The module introduces students to the emerging field of explainable machine learning and teaches them to work up results from recent research. To this end, the students will read up on a sub-field, prepare a seminar report, and present their work at the end of the term to their colleagues.

Topics cover different aspects of the explainability of machine learning methods for the application in computer security in particular.

Schedule

DateStep
Tue, 18. April, 9:45–11:15Primer on academic writing, assignment of topics
Thu, 27. AprilArrange appointments with assistant
Tue, 02. May - Fri, 05. May1st individual meeting (First overview, ToC)
Mon, 05. June - Fri, 09. June2nd individual meeting (Feedback on first draft of the report)
Wed, 28. JuneSubmit final paper
Mon, 10. JulySubmit review for fellow students
Fri, 14. JulyEnd of discussion phase
Fri, 21. JulySubmit camera-ready version of your paper
Fri, 28. JulyPresentation at final colloquium

Matrix Chat

News about the seminar, potential updates to the schedule, and additional material are distributed using the course's matrix room. Moreover, matrix enables students to discuss topics and solution approaches.

You find the link to the matrix room on ILIAS.

Topics

Every student may choose one of the following topics. For each of these, we additionally provide two recent top-tier publications that you should use as a starting point for your own research. For the seminar and your final report, you should not merely summarize that paper, but try to go beyond and arrive at your own conclusions.

Moreover, all of these papers come with open-source implementations. Play around with these and include the lessons learned in your report.