MSRI- Geometry and Representation Theory of Tensors for Computer Science, Statistics, and other areas

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    Induction for the rank of tensors

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    (e) the UDM case: some selected statistical blind identification approaches, all involving tensors. Local identifiability and numerical algorithms (including BIOME and FOOBI).

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  3. Title:
    Ch 9: Spaces of tensors admitting normal forms

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  4. Title:
    Introduction to the study of G-varieties via desingularizations by homogeneous vector bundles

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    (d) the invertible case: Independent Component Analysis - optimization criteria and some numerical algorithms

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    Nonnegative hypermatrices, symmetric tensors

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    What do the words "ACM", "Gorenstein", and " rational singularites" mean and why are these properties useful?

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  8. Title:
    (a) general statements on linear mixtures of random variables, (b)cumulants, (c) tensors

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  9. Title:
    The variety of principal minors of symmetric matrices

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  10. Title:
    Ch 8: Rank vs border rank of tensors and symmetric tensors

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  11. Title:
    Ch 7. An algorithm for explicitly writing down polynomials in a given submodule of the space of polynomials. Further combinatorics of Young tableaux. Working with tensors in factored vs. expanded form.

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  12. Title:
    § 6.1,6.2,6.6,6.7 The Alexander-Hirshowitz theorem and dimensions of secant varieties of Segre varieties

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    Non-commutative harmonic analysis in machine learning

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  14. Title:
    Uniqueness of tensor decomposition, direct sum conjecture

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  15. Title:
    § 5.6 Equations III: Strassen's equations and variants

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    § 5.4, 5.5 Equations II: inheritance, and prolongation

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  17. Title:
    What are graph states?

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  18. Title:
    Hyperdeterminants and optimal approximability

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  19. Title:
    § 5.1-5.3 Equations for secant varieties I: special Segre varieties, subspace varieties, flattenings

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  20. Title:
    finish Ch 4 (Littlewood-Richardson rule and other handy formulas, more decompositions of spaces of tensors)

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