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

When and where

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
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© AG Schreyer