This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterization of conditional independence, the learning of graphical models with latent variables, and extensions to the influence diagram formalism as well as important application fields, such as the control of vehicles, bioinformatics and medicine.
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ISBN | 9783540689942 |
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Sprache | eng |
Cover | B, Probability Theory and Stochastic Processes, Discrete Mathematics, Mathematical Modeling and Industrial Mathematics, Mathematical and Computational Engineering, Artificial Intelligence, Probability Theory, Mathematical and Computational Engineering Applications, engineering, Probabilities, Mathematical models, Applied mathematics, Engineering mathematics, Stochastics, Mathematical modelling, Maths for engineers, Fester Einband |
Verlag | Springer Nature EN |
Jahr | 2007 |
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