Mathematical Theories of Machine Learning - Theory and Applications by Bin Shi & S. S. Iyengar

Author:Bin Shi & S. S. Iyengar
Language: eng
Format: epub
ISBN: 9783030170769
Publisher: Springer International Publishing

7.2 Notations and Preliminaries

For the sake of completeness, we present necessary notations and review important definitions some of which defined earlier in Chap. 5 and will be used later in our analysis. Let be the vector space of real-valued twice-continuously differentiable functions. Let ∇ be the gradient operator and ∇2 be the Hessian operator. Let ∥⋅∥2 be the Euclidean norm in . Let μ be the Lebesgue measure in .

Definition 7.1 (Global Gradient Lipschitz Continuity Condition)

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