Titlebook: Efficient Learning Machines; Theories, Concepts, Mariette Awad,Rahul Khanna Book‘‘‘‘‘‘‘‘ 2015 The Editor(s) (if applicable) and The Author

Cocker

轻触

978-1-4302-5989-3The Editor(s) (if applicable) and The Author(s) 2015

跳脱衣舞的人

Collar

传染

Was tun, wenn alles zu spät ist? learning model. SVM offers a principled approach to problems because of its mathematical foundation in statistical learning theory. SVM constructs its solution in terms of a subset of the training input. SVM has been extensively used for classification, regression, novelty detection tasks, and feat

PALMY

Ergots

https://doi.org/10.1007/978-3-658-03215-9erize the observations as a parametric random process, the parameters of which should be estimated, using a well-defined approach. This allows us to construct a theoretical model of the underlying process that enables us to predict the process output as well as distinguish the statistical properties

BRIBE

Betriebsablauf-orientiertes MUM,ems are adaptive, evolutionary, distributed (decentralized), reactive, and aware of their environment. . (or .) is a field of study that draws its inspiration from the sophistication of the natural world in adapting to environmental changes through self-management, self-organization, and self-learni

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LURE

https://doi.org/10.1007/978-3-642-92280-0nificant discoveries in neuroscience and advancements in computing technology. Among these models, . (CAs) have emerged as a biologically inspired approach, modeled after the human visual cortex, which stores sequences of patterns in an invariant form and which recalls those patterns autoassociative