by Abdelhamid Mellouk, Abdennacer Chebira
Publisher: InTech 2009
Number of pages: 450
Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, 3d shape classification and retrieval, genetic network programming with reinforcement learning, heuristic dynamic programming, and more.
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by Csaba Szepesvari - Morgan and Claypool Publishers
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
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This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. This manuscript aims to find a good balance between theory and practice.
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Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning ...
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