This lecture (6 ECTS) will cover optimization methods that typically appear in machine learning. Most importantly, we will discuss different (stochastic) versions of gradient descent methods and their applications in machine learning.
Felix Benning, Prof. Dr. Simon Weißmann
Tuesday, B4, D 007 Seminarraum 2 (B 6, 27–29 Bauteil D)
Thursday, B3, D 007 Seminarraum 2 (B 6, 27–29 Bauteil D)
every second Thursday (starting on 2 March 2023)
Sheet 1 (correction in Exercise 1 (i))
Sheet 4 (Update 31.03.: GitHub classroom link)
Sheet 6 Replacement: Pytorch Optimizer
Lecture Notes (work in progress in parallel to this course, latest update: 01.06.2023)
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