Tensors in Computer Science
- There is a dedicated webpage for the exercises and the exercise sessions, here.
If a matrix is a square filled with numbers, then a higher-order tensor is an n-dimensional cube filled with numbers. Recent years have seen a dramatic rise of interest by computer scientists in the mathematics of higher-order tensors. The notion of matrix rank can be generalized to higher-order tensors. While matrix rank can be efficiently computed by, say, Gaussian eliminination, computing the rank of a tensor of order 3 is NP-hard. The question of the complexity of matrix multiplication can be formulated as the question of the rank of a certain tensor. We will mainly focus on applications in complexity theory and quantum computation. In particular, it is very unlikely that we will deal with applications in machine learning.
- Prof. Dr. Markus Bläser, Email: mblaeser at cs.uni-saarland.de
- Prof. Dr. Frank-Olaf Schreyer, Email: schreyer at math.uni-sb.de
Lectures take place every Tuesday and Wednesday, 10:00-12:00, in Hörsaal III (0.03.1), Gebäude E1 3.
Oral exams in the semester break.
For news about the exercises and for the exercise sheets, visit the dedicated webpage.
| |
Fabio Tanturri Zi. 429, Geb. E2 4 D-66123 Saarbrücken Tel. +49(0)681/302-2030 This email address is being protected from spambots. You need JavaScript enabled to view it. |