Learning Motor Skills, Jens Kober; Jan Peters

Автор: Hastie
Название: Statistical Learning with Sparsity
ISBN: 1498712169 ISBN-13(EAN): 9781498712163
Издательство: Taylor&Francis
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Цена: 112290.00 T
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Описание:

Discover New Methods for Dealing with High-Dimensional Data

A sparse statistical model has only a small number of nonzero parameters or weights; therefore, it is much easier to estimate and interpret than a dense model. Statistical Learning with Sparsity: The Lasso and Generalizations presents methods that exploit sparsity to help recover the underlying signal in a set of data.

Top experts in this rapidly evolving field, the authors describe the lasso for linear regression and a simple coordinate descent algorithm for its computation. They discuss the application of ℓ1 penalties to generalized linear models and support vector machines, cover generalized penalties such as the elastic net and group lasso, and review numerical methods for optimization. They also present statistical inference methods for fitted (lasso) models, including the bootstrap, Bayesian methods, and recently developed approaches. In addition, the book examines matrix decomposition, sparse multivariate analysis, graphical models, and compressed sensing. It concludes with a survey of theoretical results for the lasso.

In this age of big data, the number of features measured on a person or object can be large and might be larger than the number of observations. This book shows how the sparsity assumption allows us to tackle these problems and extract useful and reproducible patterns from big datasets. Data analysts, computer scientists, and theorists will appreciate this thorough and up-to-date treatment of sparse statistical modeling.

Автор: Przemys?aw R??ewski; Emma Kusztina; Ryszard Tadeus
Название: Intelligent Open Learning Systems
ISBN: 3642270786 ISBN-13(EAN): 9783642270789
Издательство: Springer
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Цена: 144410.00 T
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Описание: IOLSs enhance traditional online teaching methods by applying artificial intelligence and cognitive science. This book moves from analyzing OLSs and the role of the teacher, to knowledge modeling and ways of transferring competence in the virtual laboratory.

Автор: Jens Kober; Jan Peters
Название: Learning Motor Skills
ISBN: 3319031937 ISBN-13(EAN): 9783319031934
Издательство: Springer
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Цена: 130430.00 T
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Описание: This overview by an award-winning researcher of the ways reinforcement learning can be applied to robotics includes new algorithms and applications. It assesses their success in benchmark tasks such as darts, table tennis, and ball-throwing and bouncing.

Автор: Olivier Sigaud; Jan Peters
Название: From Motor Learning to Interaction Learning in Robots
ISBN: 3642262325 ISBN-13(EAN): 9783642262326
Издательство: Springer
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Цена: 186330.00 T
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Описание: This book is largely based on the successful workshop "From motor to interaction learning in robots" held at the IEEE/RSJ International Conference on Intelligent Robot Systems. It presents recent research in motor learning and interaction learning in robots.

Автор: Bir Bhanu; Ajay Kumar
Название: Deep Learning for Biometrics
ISBN: 3319616560 ISBN-13(EAN): 9783319616568
Издательство: Springer
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Цена: 130430.00 T
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Описание: Issues of biometrics security are also examined.Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities;

Название: Frontiers in Data Science
ISBN: 1498799329 ISBN-13(EAN): 9781498799324
Издательство: Taylor&Francis
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Цена: 127600.00 T
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Описание: Frontiers in Data Science deals with philosophical and practical results in Data Science. A broad definition of Data Science describes the process of analyzing data to transform data into insights. This also involves asking philosophical, legal and social questions in the context of data generation and analysis.

Автор: Philipp Cimiano
Название: Ontology Learning and Population from Text
ISBN: 1441940324 ISBN-13(EAN): 9781441940322
Издательство: Springer
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Цена: 121110.00 T
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Описание: Preliminaries.- Ontologies.- Ontology Learning from Text.- Basics.- Datasets.- Methods and Applications.- Concept Hierarchy Induction.- Learning Attributes and Relations.- Population.- Applications.- Conclusion.- Contribution and Outlook.- Concluding Remarks.

Автор: Jose C. Principe
Название: Information Theoretic Learning
ISBN: 1461425859 ISBN-13(EAN): 9781461425854
Издательство: Springer
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Цена: 144410.00 T
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Описание: This book is the first cohesive treatment of ITL algorithms to adapt linear or nonlinear learning machines both in supervised and unsupervised paradigms. It compares the performance of ITL algorithms with the second order counterparts in many applications.

Автор: Olivier Sigaud; Jan Peters
Название: From Motor Learning to Interaction Learning in Robots
ISBN: 3642051804 ISBN-13(EAN): 9783642051807
Издательство: Springer
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Цена: 278580.00 T
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Описание: This book is largely based on the successful workshop "From motor to interaction learning in robots" held at the IEEE/RSJ International Conference on Intelligent Robot Systems. It presents recent research in motor learning and interaction learning in robots.

Автор: J?rgen Beyerer; Oliver Niggemann; Christian K?hner
Название: Machine Learning for Cyber Physical Systems
ISBN: 3662538059 ISBN-13(EAN): 9783662538050
Издательство: Springer
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Цена: 158380.00 T
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Описание: The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papers from the international Conference ML4CPS – Machine Learning for Cyber Physical Systems, which was held in Karlsruhe, September 29th, 2016. Cyber Physical Systems are characterized by their ability to adapt and to learn: They analyze their environment and, based on observations, they learn patterns, correlations and predictive models. Typical applications are condition monitoring, predictive maintenance, image processing and diagnosis. Machine Learning is the key technology for these developments.

Автор: Hans-J?rgen Zimmermann; Georgios Tselentis; Maarte
Название: Advances in Computational Intelligence and Learning
ISBN: 0792376455 ISBN-13(EAN): 9780792376453
Издательство: Springer
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Цена: 149060.00 T
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Описание: Presents the developments and applications in the area of Computational Intelligence, which describes methods and approaches that mimic biologically intelligent behavior in order to solve problems that have been difficult to solve by classical mathematics.

Автор: Ryan J. Urbanowicz; Will N. Browne
Название: Introduction to Learning Classifier Systems
ISBN: 3662550067 ISBN-13(EAN): 9783662550069
Издательство: Springer
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Цена: 46570.00 T
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Описание: This is an accessible introduction to Learning Classifier Systems (LCS) for undergraduate and postgraduate students, data analysts, and machine learning practitioners.