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Einrichtungen >> Fakultät Wirtschaftsinformatik / Angewandte Informatik >> Bereich Angewandte Informatik >> Lehrstuhl für Erklärbares Maschinelles Lernen >>
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xAI-Proj-M: Masterprojekt Erklärbares Maschinelles Lernen- Dozentinnen/Dozenten
- Francesco Di Salvo, Prof. Dr. Christian Ledig
- Angaben
- [PJS]
Rein Präsenz
4,00 SWS, Unterrichtssprache Englisch
Zeit und Ort: Mi 14:00 - 18:00, WE5/05.005
- Voraussetzungen / Organisatorisches
- Interest and registration
Registration via central registration or email to francesco.di-salvo@uni-bamberg.de with matriculation number, degree program, and completed ML-related modules before October 18, 2024.
Eligibility
M.Sc. AI, M.Sc. CitH, M.Sc. WI
Requirements
Successfully passed the exam xAI-DL-M, xAI-MML-M, KogSys-ML-M or AI-KI-B (Introduction to AI)
VC-Course: https://vc.uni-bamberg.de/course/view.php?id=70916
Beneficiaries
Critical thinking, hands-on knowledge in machine learning and deep learning, fundamental aspects of medical imaging or healthcare technology, scientific writing and presenting, LaTeX.
- Inhalt
- Topic:
Domain Generalization for Robust Machine Learning
Overview:
Machine learning has become increasingly popular in recent years, with applications spanning healthcare, finance, energy, and numerous other sectors. Despite its success, several critical challenges remain that must be addressed before machine learning models can be reliably and robustly deployed in real-world scenarios. One such challenge is Domain Generalization (DG), which focuses on training models that can generalize to unseen or out-of-distribution data without exposure to the test domain. This is essential for creating models that perform reliably in real-world settings. In teams of 3-4, students will explore this open problem, building on state-of-the-art methods. They will formulate research questions, investigate solutions, and validate their findings with guidance from the instructor.
Initial meeting: 16/10/24 (General info, Q&A and preliminary overview - not mandatory)
Kick-off: 23/10/24 (mandatory for participants)
- Englischsprachige Informationen:
- Title:
- xAI-Proj-M: Master Project Explainable Machine Learning
- Credits: 6
- Zusätzliche Informationen
- Erwartete Teilnehmerzahl: 12
Hinweis für Web-Redakteure:
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