Twin Support Vector Machines, Jayadeva; Reshma Khemchandani; Suresh Chandra

Автор: Ingo Steinwart; Andreas Christmann
Название: Support Vector Machines
ISBN: 1489989633 ISBN-13(EAN): 9781489989635
Издательство: Springer
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Цена: 20962.00 р.
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Описание: In a nutshell, we identify at least three reasons for the success of SVMs: their ability to learn well with only a very small number of free parameters, their robustness against several types of model violations and outliers, and last but not least their computational e?ciency compared with several other methods.

Автор: Murty
Название: Support Vector Machines and Perceptrons
ISBN: 3319410628 ISBN-13(EAN): 9783319410623
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This work reviews the state of the art in SVM and perceptron classifiers. A Support Vector Machine (SVM) is easily the most popular tool for dealing with a variety of machine-learning tasks, including classification. SVMs are associated with maximizing the margin between two classes. The concerned optimization problem is a convex optimization guaranteeing a globally optimal solution. The weight vector associated with SVM is obtained by a linear combination of some of the boundary and noisy vectors. Further, when the data are not linearly separable, tuning the coefficient of the regularization term becomes crucial. Even though SVMs have popularized the kernel trick, in most of the practical applications that are high-dimensional, linear SVMs are popularly used. The text examines applications to social and information networks. The work also discusses another popular linear classifier, the perceptron, and compares its performance with that of the SVM in different application areas.>

Название: Least Squares Support Vector Machin
ISBN: 9812381511 ISBN-13(EAN): 9789812381514
Издательство: World Scientific Publishing
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Описание: An examination of least squares support vector machines (LS-SVMs) which are reformulations to standard SVMs. The authors explain the natural links between LS-SVM classifiers and kernel Fisher discriminant analysis. Bayesian inference of LS-SVM models is also discussed.

Автор: Kelly John E., Hamm Steve
Название: Smart Machines: IBM`s Watson and the Era of Cognitive Computing
ISBN: 023116856X ISBN-13(EAN): 9780231168564
Издательство: Wiley
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Цена: 3008.00 р.
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Описание:

We are crossing a new frontier in the evolution of computing and entering the era of cognitive systems. The victory of IBM's Watson on the television quiz show Jeopardy revealed how scientists and engineers at IBM and elsewhere are pushing the boundaries of science and technology to create machines that sense, learn, reason, and interact with people in new ways to provide insight and advice.

In Smart Machines, John E. Kelly III, director of IBM Research, and Steve Hamm, a writer at IBM and a former business and technology journalist, introduce the fascinating world of "cognitive systems" to general audiences and provide a window into the future of computing. Cognitive systems promise to penetrate complexity and assist people and organizations in better decision making. They can help doctors evaluate and treat patients, augment the ways we see, anticipate major weather events, and contribute to smarter urban planning. Kelly and Hamm's comprehensive perspective describes this technology inside and out and explains how it will help us conquer the harnessing and understanding of "big data," one of the major computing challenges facing businesses and governments in the coming decades. Absorbing and impassioned, their book will inspire governments, academics, and the global tech industry to work together to power this exciting wave in innovation.

Автор: Mario Neto Borges; Nival Nunes de Almeida
Название: Intelligent Educational Machines
ISBN: 3642079539 ISBN-13(EAN): 9783642079535
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book presents recent advances in intelligent educational machines. It will be of particular interest to engineers, researchers, and graduate students in Computational Intelligence.