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Seminar – Mathematik im Maschniellen Lernen (Prof. Dr. Ch. Lubich, WS 2023/24)

Aktuelles

Wichtige Links

• URM
• Alma

Termine

• 14.11.2023
• 21.11.2023
• 18.11.2023
• 05.12.2023
• 12.12.2023
• 19.12.2023

Vorträge

Datum und Uhrzeit	Thema	Vortragende	Bibliographie	Handout
14.11.2023	Singular value decomposition	Christian Lubich	[1]
14.11.2023	Changes in A⁻1 fromchanges in A + Interlacing eigenvalues and low-rank signals	Anna Maggioli	[1]
21.11.2023	Compressed sensing and matrix completion	Lukas Ringel	[1]
21.11.2023	Deep neural networks	Yutain Zhang	[1]
28.11.2023	Convolutional neural networks	Leo Gönner	[1]
28.11.2023	Back propagation and chain rule	Veronika Reimchen	[1]
05.12.2023	Gradient decsent + Hyperparameters	Clemens Teupe	[1]
05.12.2023	Stochastic gradient decsent	Tobias Winkler	[1]
12.12.2023	Low-rank decsent	Long Nguyen	[2]
12.12.2023	Graphs, Laplacians and Kirchhofs law	Laura Herb	[1]
19.12.2023	Clustering by spectral methids & k-means (+ completion of rank 1 matrices -> optional)	Lucas Weyer	[1]

Literatur

• [1] Strang, Gilbert, Linear Algebra and Learning from Data, Wellesley-Cambridge Press, 2019.
• [2] S. Schotthöfer, E. Zangrando, J. Kusch, G. Ceruti, F. Tudisco, Low-rank lottery tickets: finding efficient low-rank neural networks via matrix differential equations, Advances in Neural Information Processing Systems 35, 20051-20063.

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