Posted by **tanas.olesya** at Nov. 25, 2014

English | September 30, 1998 | ISBN: 0471030031 | 740 pages | PDF | 26 MB

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data.

Posted by **danrop** at June 26, 2007

John Wiley & Sons | ISBN : 0471030031 | Year - 1998 | DjVu | 5.8 MB | 732 Pages

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.

Posted by **tanas.olesya** at July 8, 2016

English | 19 Nov. 1999 | ISBN: 0387987800 | 334 Pages | PDF | 10 MB

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization.

Posted by **AlenMiler** at Dec. 28, 2015

English | June 27, 1986 | ISBN: 0521245850, 0521019001 | 412 Pages | PDF | 67 MB

The word holor is a term coined by the authors to describe a mathematical entity that is made up of one or more independent quantities, and includes complex numbers, scalars, vectors, matrices, tensors, quaternions, and other hypernumbers.

Posted by **tanas.olesya** at Aug. 6, 2015

English | June 27, 1986 | ISBN: 0521245850, 0521019001 | 412 Pages | PDF | 67 MB

The word holor is a term coined by the authors to describe a mathematical entity that is made up of one or more independent quantities, and includes complex numbers, scalars, vectors, matrices, tensors, quaternions, and other hypernumbers.

Posted by **BUGSY** at June 22, 2015

English | Nov 19, 1999 | ISBN: 0387987800 | 334 Pages | PDF | 10 MB

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data.

Posted by **tanas.olesya** at Oct. 18, 2014

Springer; 2nd edition | November 19, 1999 | English | ISBN: 0387987800 | 334 pages | PDF | 10 MB

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics.

Posted by **interes** at July 15, 2014

English | ISBN: 1461469457 | 2013 | 265 pages | PDF | 1,7 MB

The approximation of functions by linear positive operators is an important research topic in general mathematics and it also provides powerful tools to application areas such as computer-aided geometric design, numerical analysis, and solutions of differential equations. q-Calculus is a generalization of many subjects, such as hypergeometric series, complex analysis, and particle physics.

Posted by **ph4rr3l** at Oct. 29, 2013

English | ISBN: 1461469457 | 2013 | 265 pages | PDF | 3 MB

The approximation of functions by linear positive operators is an important research topic in general mathematics and it also provides powerful tools to application areas such as computer-aided geometric design, numerical analysis, and solutions of differential equations. q-Calculus is a generalization of many subjects, such as hypergeometric series, complex analysis, and particle physics. This monograph is an introduction to combining approximation theory and q-Calculus with applications, by using well- known operators. The presentation is systematic and the authors include a brief summary of the notations and basic definitions of q-calculus before delving into more advanced material. The many applications of q-calculus in the theory of approximation, especially on various operators, which includes convergence of operators to functions in real and complex domain forms the gist of the book.

Posted by **Direktor69** at Aug. 24, 2013

ISBN: 0387987800 | edition 1999 | PDF | 334 pages | 10 mb

The aim of this book is to discuss the fundamental ideas which lie behind the statistical theory of learning and generalization. It considers learning as a general problem of function estimation based on empirical data. Omitting proofs and technical details, the author concentrates on discussing the main results of learning theory and their connections to fundamental problems in statistics.