Interaction between Light and Matter
Seminar: Advance topics of machine learning
Winter Semester 2020/21Dr. Dirk-André Deckert
Room: ZOOM Time: Thursdays, 16-18h
This seminar is intended to be a topical continuation of last semester's introductory course material "Mathematic(al Statistic)s and Applications of Machine Learning". Topics will be discussed, decided and assigned during the first meeting. They will have an emphasis on mathematics and applications and, depending on interest and background, may range from classic to modern literature including, e.g., PAC framework, generalization bounds, approximation & representation, artificial/convolutional/spiking/recurrent and generative adversarial networks, approximation & representation & optimization, deep learning, boosting, probabilistic/causal reasoning, Haar cascades, landmark detection, natural language processing, vector embeddings, etc... Please prepare topic suggestions.
Date | Speaker | Topics | Slides |
---|---|---|---|
19.11.20 | Niklas Weber | Word2Vec | PDF, IPYNB |
26.11.20 | Henry Kleinedam | Reinforcement learning | |
03.12.20 | Yannick Limmer | Bayesian Statistics and Bayesian Networks | |
10.12.20 | Simon Heydrowsky | Cluster Analysis | |
17.12.20 | Florian Geys | Decision Trees | |
07.01.21 | Cornelius Schwab | Dimensionality reduction | |
14.01.21 | Hares Khalilzad Bahadori | Haar Cascades | |
21.01.21 | Jago Silberbauer | Generative Adversarial Networks | |
28.01.21 | Christian Rehpenn | Auto-encoder | |
04.02.21 | Jakob Ullmann | Approximation Theory |