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Learning with Partially Labeled and Interdependent Data, Massih-Reza Amini; Nicolas Usunier


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Автор: Massih-Reza Amini; Nicolas Usunier
Название:  Learning with Partially Labeled and Interdependent Data
ISBN: 9783319353906
Издательство: Springer
Классификация:


ISBN-10: 331935390X
Обложка/Формат: Paperback
Страницы: 106
Вес: 0.18 кг.
Дата издания: 09.10.2016
Язык: English
Размер: 234 x 156 x 7
Основная тема: Computer Science
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data.


Learning with Partially Labeled and Interdependent Data

Автор: Massih-Reza Amini; Nicolas Usunier
Название: Learning with Partially Labeled and Interdependent Data
ISBN: 3319157256 ISBN-13(EAN): 9783319157252
Издательство: Springer
Рейтинг:
Цена: 11179.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book develops two key machine learning principles: the semi-supervised paradigm and learning with interdependent data.

Metric Methods for Analyzing Partially Ranked Data

Автор: Douglas E. Critchlow
Название: Metric Methods for Analyzing Partially Ranked Data
ISBN: 0387962883 ISBN-13(EAN): 9780387962887
Издательство: Springer
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Цена: 19564.00 р.
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Описание: A full ranking of n items is simply an ordering of all these items, of the form: first choice, second choice, *. The problem thus becomes one of ex- tending metrics on the permutation group to metrics on a coset space of the permutation group.

Partially Linear Models

Автор: Wolfgang H?rdle; Hua Liang; Jiti Gao
Название: Partially Linear Models
ISBN: 3790813001 ISBN-13(EAN): 9783790813005
Издательство: Springer
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Цена: 16070.00 р.
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Описание: In the last ten years, there has been increasing interest and activity in the general area of partially linear regression smoothing in statistics.

Feedback Strategies for Partially Observable Stochastic Systems

Автор: Y. Yavin
Название: Feedback Strategies for Partially Observable Stochastic Systems
ISBN: 3540122087 ISBN-13(EAN): 9783540122081
Издательство: Springer
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Цена: 12157.00 р.
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Partially Observable Linear Systems Under Dependent Noises

Автор: Agamirza E. Bashirov
Название: Partially Observable Linear Systems Under Dependent Noises
ISBN: 3034894074 ISBN-13(EAN): 9783034894074
Издательство: Springer
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Цена: 13974.00 р.
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Описание:

Noise is a rich concept playing an underlying role in human activity. Consideration of the noise phenomenon in arts and sciences, respectively, makes the distinction between both domains more obvious. Artists create "deliberate noise" ; the masterpieces of literature, music, modern fine art etc. are those where a clear idea, traditionally related to such concepts as love, is presented under a skilful veil of "deliberate noise." On the contrary, sciences fight against noise; a scientific discovery is a law of nature extracted from a noisy medium and refined.

This book discusses the methods of fighting against noise. It can be regarded as a mathematical view of specific engineering problems with known and new methods of control and estimation in noisy media.

The main feature of this book is the investigation of stochastic optimal control and estimation problems with the noise processes acting dependently on the state (or signal) and observation systems. While multiple early and recent findings on the subject have been obtained and challenging problems remain to be solved, this subject has not yet been dealt with systematically nor properly investigated. The discussion is given for infinite dimensional systems, but within the linear quadratic framework for continuous and finite time horizon. In order to make this book self-contained, some background material is provided.

Consequently, the target readers of this book are both applied mathematicians and theoretically oriented engineers who are designing new technology, as well as students of the related branches. The book may also be used as a reference manual in that part of functional analysis that is needed for problems of infinite dimensional linear systems theory.


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