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The three chapters of this book are entitled Basic Concepts, Tensor Norms, and Special Topics. The first may serve as part of an introductory course in Functional Analysis since it… Read more
AI & BIG DATA
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Tensor Norms. Definition and Examples. The Five Basic Lemmas. Grothendieck's Inequality. Dual Tensor Norms. The Bounded Approximation Property. The Representation Theorem for Maximal Operator Ideals. (p-q)-Factorable Operators. (p-q)-Dominated Operators. Projective and Injective Tensor Norms. Accessible Tensor Norms and Operator Ideals. Minimal Operator Ideals. Lgp-Spaces. Stable Measures. Composition of Accessible Operator Ideals. More About Lp and Hilbert Spaces. Grothendieck's Fourteen Natural Norms.
Special Topics. More Tensor Norms. The Calculus of Traced Tensor Norms. The Vector Valued Fourier Transform. Pisier's Factorization Theorem. Mixing Operators. The Radon-Nikodym Property for Tensor Norms and Reflexivity. Tensorstable Operator Ideals. Tensor Norm Techniques for Locally Convex Spaces.
Appendices. References. Index.
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