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Subject offerings of new and developing areas of knowledge in computer science intended to augment the existing curriculum. See Class Schedule or departmental course information for topics and prerequisites. Course Information: May be repeated in the same or separate terms if topics vary.

The course will cover theory, algorithms, and some applications of tensors and tensor decompositions. The course will first review and explore relevant topics in numerical linear algebra and nonlinear optimization, including iterative solvers and preconditioning, low rank approximation, as well as randomized techniques (sketching). Properties of decompositions and eigenvalues of tensors, as well as algorithms for computing these will be covered in detail. The course will also survey algorithms for inexact contraction of large tensor networks and methods for dynamical low-rank simulation with tensor decompositions. Prerequisites: familiarity with numerical linear algebra, and algorithms (e.g. CS 450, and CS 374 or CS 473) For up-to-date information about CS course restrictions, please see the following link: http://go.cs.illinois.edu/csregister