Human-Centric Machine Learning concerns the design of machine learning algorithms and models for interaction with humans in real-world scenarios. The seminar will cover foundational and current research on human-centric machine learning topics, namely explainability, interpretability, fairness, and interactive machine learning. We will discuss definitions, methods for achieving human-centric machine learning, and practical application cases. Students will be expected to
1) give a presentation on one subtopic of the seminar, 2) actively participate in discussing the presentations of other students, and 3) write an essay of 5-15 pages on their topic.
Frequency | Weekday | Time | Format / Place | Period |
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Module | Course | Requirements | |
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39-Inf-EGMI Ergänzungsmodul Informatik | vertiefendes Seminar 1 | Ungraded examination
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Student information |
vertiefendes Seminar 2 | Ungraded examination
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Student information | |
vertiefendes Seminar 3 | Ungraded examination
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Student information | |
vertiefendes Seminar 4 | Ungraded examination
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Student information | |
39-Inf-WP-IG Informatik & Gesellschaft (Basis) | Einführendes Seminar | Student information | |
- | Graded examination | Student information |
The binding module descriptions contain further information, including specifications on the "types of assignments" students need to complete. In cases where a module description mentions more than one kind of assignment, the respective member of the teaching staff will decide which task(s) they assign the students.
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