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Algebra and Geometry of Tensor Decomposition: Scientific Computing and Matrix Computations SeminarSeminar  March 6  12:101 p.m.  380 Soda Hall Luke Oeding, UC Berkeley Electrical Engineering and Computer Sciences (EECS) Tensors (or multidimensional matrices) represent a type of data structure that is ubiquitous in the sciences. Because of their wide use, there is much interest in understanding their fundamental properties, such as tensor decomposition and tensor rank. Tensor decomposition is a sparse representation of a tensor as a linear combination of rankone tensors, while tensor rank is the number of summands in a minimal decomposition. odedsc@cs.berkeley.edu, 5105164321 

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