AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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High-dimensional analogue: H\"older-Gauss-approximations, which can be (roughly) interpreted as the Gaussian approximation for a H\"older-norm of the high-dimensional partial sum process of the high-dimensional partial sum process is presented.
We develop a selfnormalized approach to inference for relevant changes in functional time series measured by the supremum norm. The main difficulty is that the supremum norm is not Hadamard differentiable, so standard projection-based selfnormalization does not apply and the limiting distribution may depend on the geom...
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