Titlebook: Improved Classification Rates for Localized Algorithms under Margin Conditions; Ingrid Karin Blaschzyk Book 2020 Springer Fachmedien Wiesb

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atency, consuming energy and improving privacy. As the most important technique of AI, Deep Neural Networks (DNN) has been widely used in various fields. And for those DNN based tasks, a new computing scheme named DNN model partition can further reduce the execution time. This computing scheme parti

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Discussion,of the input space, which splits the input space in a part in which cells are located close to the decision boundary and in a part in which the cells are sufficiently bounded away from it. This separation was described by a parameter . > 0 and we examined the excess risks on both parts separately.

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978-3-658-29590-5Springer Fachmedien Wiesbaden GmbH, part of Springer Nature 2020

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Ingrid Karin BlaschzykStudy in the field of natural sciences.Study in the field of statistical learning theory

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Histogram Rule: Oracle Inequality and Learning Rates,alysis of localized SVMs in Chapter 4 and highlights the main concepts that lead together with a certain splitting procedure to improved error bounds and learning rates, see Sections?3.1 and 3.2. We derive rates under margin conditions and compare them with other known rates in Section?3.3.

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Discussion,of the input space, which splits the input space in a part in which cells are located close to the decision boundary and in a part in which the cells are sufficiently bounded away from it. This separation was described by a parameter . > 0 and we examined the excess risks on both parts separately.

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