The Innermost Kernel
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Author | : Suzanne Gieser |
Publisher | : Springer Science & Business Media |
Total Pages | : 386 |
Release | : 2005-11-21 |
Genre | : Science |
ISBN | : 354026986X |
The publication of W. Pauli's Scientific Correspondence by Springer-Verlag has motivated a vast research activity on Pauli's role in modern science. This excellent treatise sheds light on the ongoing dialogue between physics and psychology.
Author | : John Shawe-Taylor |
Publisher | : Cambridge University Press |
Total Pages | : 520 |
Release | : 2004-06-28 |
Genre | : Computers |
ISBN | : 1139451618 |
Kernel methods provide a powerful and unified framework for pattern discovery, motivating algorithms that can act on general types of data (e.g. strings, vectors or text) and look for general types of relations (e.g. rankings, classifications, regressions, clusters). The application areas range from neural networks and pattern recognition to machine learning and data mining. This book, developed from lectures and tutorials, fulfils two major roles: firstly it provides practitioners with a large toolkit of algorithms, kernels and solutions ready to use for standard pattern discovery problems in fields such as bioinformatics, text analysis, image analysis. Secondly it provides an easy introduction for students and researchers to the growing field of kernel-based pattern analysis, demonstrating with examples how to handcraft an algorithm or a kernel for a new specific application, and covering all the necessary conceptual and mathematical tools to do so.
Author | : |
Publisher | : |
Total Pages | : 854 |
Release | : 1942 |
Genre | : Agriculture |
ISBN | : |
Author | : Gregory E Fasshauer |
Publisher | : World Scientific Publishing Company |
Total Pages | : 537 |
Release | : 2015-07-30 |
Genre | : Mathematics |
ISBN | : 9814630152 |
In an attempt to introduce application scientists and graduate students to the exciting topic of positive definite kernels and radial basis functions, this book presents modern theoretical results on kernel-based approximation methods and demonstrates their implementation in various settings. The authors explore the historical context of this fascinating topic and explain recent advances as strategies to address long-standing problems. Examples are drawn from fields as diverse as function approximation, spatial statistics, boundary value problems, machine learning, surrogate modeling and finance. Researchers from those and other fields can recreate the results within using the documented MATLAB code, also available through the online library. This combination of a strong theoretical foundation and accessible experimentation empowers readers to use positive definite kernels on their own problems of interest.
Author | : Geoffrey W. Bromiley |
Publisher | : Wipf and Stock Publishers |
Total Pages | : 495 |
Release | : 1998-02-04 |
Genre | : Religion |
ISBN | : 1579101720 |
ÒAn ideal historical theology, or even an introduction to it, Ò says Geoffrey Bromiley, Òlies beyond the limits of human possibility.Ó And he does not intend this volume to be an all-inclusive theological study about everybody and everything. Rather, Òthis work is composed for beginners, for inquirers, for those who know nothing or very little of the history of theology, but who want to know something, or something more.
Author | : Johan A.K. Suykens |
Publisher | : CRC Press |
Total Pages | : 528 |
Release | : 2014-10-23 |
Genre | : Computers |
ISBN | : 1482241390 |
Regularization, Optimization, Kernels, and Support Vector Machines offers a snapshot of the current state of the art of large-scale machine learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex and large-scale optimization, kernel methods, and support vector machines. Consisting of 21 chapters authored by leading researchers in machine learning, this comprehensive reference: Covers the relationship between support vector machines (SVMs) and the Lasso Discusses multi-layer SVMs Explores nonparametric feature selection, basis pursuit methods, and robust compressive sensing Describes graph-based regularization methods for single- and multi-task learning Considers regularized methods for dictionary learning and portfolio selection Addresses non-negative matrix factorization Examines low-rank matrix and tensor-based models Presents advanced kernel methods for batch and online machine learning, system identification, domain adaptation, and image processing Tackles large-scale algorithms including conditional gradient methods, (non-convex) proximal techniques, and stochastic gradient descent Regularization, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing, statistical learning, and related areas.
Author | : Nello Cristianini |
Publisher | : Cambridge University Press |
Total Pages | : 216 |
Release | : 2000-03-23 |
Genre | : Computers |
ISBN | : 9780521780193 |
This is a comprehensive introduction to Support Vector Machines, a generation learning system based on advances in statistical learning theory.
Author | : Michael O'Boyle |
Publisher | : Springer Science & Business Media |
Total Pages | : 256 |
Release | : 2012-03-09 |
Genre | : Computers |
ISBN | : 3642286518 |
This book constitutes the proceedings of the 21st International Conference on Compiler Construction, CC 2012, held as part of the joint European Conference on Theory and Practice of Software, ETAPS 2012, which took place in Tallinn, Estonia, in March/April 2012. The 13 papers presented in this book were carefully reviewed and selected from 51 submissions. They are organized in topical sections named: GPU optimisation, program analysis, objects and components, and dynamic analysis and runtime support.
Author | : Gustavo Camps-Valls |
Publisher | : IGI Global |
Total Pages | : 431 |
Release | : 2007-01-01 |
Genre | : Technology & Engineering |
ISBN | : 1599040425 |
"This book presents an extensive introduction to the field of kernel methods and real world applications. The book is organized in four parts: the first is an introductory chapter providing a framework of kernel methods; the others address Bioegineering, Signal Processing and Communications and Image Processing"--Provided by publisher.
Author | : Thomas Grtner |
Publisher | : World Scientific |
Total Pages | : 216 |
Release | : 2008 |
Genre | : Computers |
ISBN | : 9812814558 |
This book provides a unique treatment of an important area of machine learning and answers the question of how kernel methods can be applied to structured data. Kernel methods are a class of state-of-the-art learning algorithms that exhibit excellent learning results in several application domains. Originally, kernel methods were developed with data in mind that can easily be embedded in a Euclidean vector space. Much real-world data does not have this property but is inherently structured. An example of such data, often consulted in the book, is the (2D) graph structure of molecules formed by their atoms and bonds. The book guides the reader from the basics of kernel methods to advanced algorithms and kernel design for structured data. It is thus useful for readers who seek an entry point into the field as well as experienced researchers.