Explainable Machine Learning

Overview

SemesterWinter 2020
Course typeBlock Seminar
LecturerJun.-Prof. Dr. Wressnegger
AudienceInformatik Master & Bachelor
Credits4 ECTS
Room148, Building 50.34
LanguageEnglish or German
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
TBAPrimer on academic writing, assignment of topics
TBAArrange appointment with assistant
TBAIndividual meetings with assistant
TBASubmit final paper
TBASubmit review for fellow students
TBASubmit camera-ready version of your paper
TBAPresentation at final colloquium

Mailing List

News about the seminar, potential updates to the schedule, and additional material are distributed using a separate mailing list. Moreover, the list enables students to discuss topics of the seminar.

You can subscribe here.