Автор: Hastie Название: Statistical Learning with Sparsity ISBN: 1498712169 ISBN-13(EAN): 9781498712163 Издательство: Taylor&Francis Рейтинг: Цена: 16843.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Rynson W.H. Lau; Qing Li; Ronnie Cheung; Wenyin Li Название: Advances in Web-Based Learning - ICWL 2005 ISBN: 3540278958 ISBN-13(EAN): 9783540278955 Издательство: Springer Рейтинг: Цена: 13275.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Constitutes the refereed proceedings of the 4th International Conference on Web-Based Learning, ICWL 2005, held in Hong Kong, China in July/August 2005. The papers in this book are organized in topical sections on e-learning platforms and tools; learning resource deployment, organization, and management; practice and experience sharing, and more.
Автор: Jens Kober; Jan Peters Название: Learning Motor Skills ISBN: 3319031937 ISBN-13(EAN): 9783319031934 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Описание: Proceedings of the NATO Advanced Research Workshop on Knowledge Acquisition in the Domain of Physics and Intelligent Learning Environments, held in Lyon, France, July 8-12, 1990
Автор: Olivier Sigaud; Jan Peters Название: From Motor Learning to Interaction Learning in Robots ISBN: 3642051804 ISBN-13(EAN): 9783642051807 Издательство: Springer Рейтинг: Цена: 41787.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Olivier Sigaud; Jan Peters Название: From Motor Learning to Interaction Learning in Robots ISBN: 3642262325 ISBN-13(EAN): 9783642262326 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: Hans-J?rgen Zimmermann; Georgios Tselentis; Maarte Название: Advances in Computational Intelligence and Learning ISBN: 0792376455 ISBN-13(EAN): 9780792376453 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This is an accessible introduction to Learning Classifier Systems (LCS) for undergraduate and postgraduate students, data analysts, and machine learning practitioners.
Автор: Philipp Cimiano Название: Ontology Learning and Population from Text ISBN: 1441940324 ISBN-13(EAN): 9781441940322 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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 Рейтинг: Цена: 21661.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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: J?rgen Beyerer; Oliver Niggemann; Christian K?hner Название: Machine Learning for Cyber Physical Systems ISBN: 3662538059 ISBN-13(EAN): 9783662538050 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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