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Die folgenden Informationen sind noch nicht freigegeben und deshalb unverbindlich: Statistical Machine Learning SemesterWiSe 2025 / 26 Lecturer Merle Behr Type of course (Veranstaltungsart) Vorlesung German title Statistisches Maschinelles Lernen Contents This course covers the mathematical and statistical foundations of machine learning (ML). Various approaches and associated analysis tools for the theoretical investigation of ML methods are covered. Possible topics include the theoretical and statistical investigation of nearest-neighbor methods, decision tree-based methods, penalized linear regression, kernel methods, ensemble methods and neural networks. Further possible topics are causal inference and conformal prediction. An introduction to empirical process theory is also provided for the theoretical analysis of these methods. Literature The course will be based on various material, including journal articles. Some basic references are "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman, Springer, 2009; "A Probabilistic Theory of Pattern Recognition" by Luc Devroye , László Györfi , Gábor Lugosi, Springer, 2013 Recommended previous knowledge Linear algebra, analysis, and probability theory. Time/Date Thursdays 12:15 - 14:00 (lecture) and Fridays 10:15 - 12:00 (tutorial) Location BA.621 (Bajuwarenstraße 4, FIDS) Course homepage https://elearning.uni-regensburg.de/course/view.php?id=71905 (Disclaimer: Dieser Link wurde automatisch erzeugt und ist evtl. extern) Registration
MV ECTS 6 |