A Theory of Learning and Generalization PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download A Theory of Learning and Generalization PDF full book. Access full book title A Theory of Learning and Generalization by Mathukumalli Vidyasagar. Download full books in PDF and EPUB format.
Author: Mathukumalli Vidyasagar
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 408
Get Book Here
Book Description
A Theory of Learning and Generalization provides a formal mathematical theory for addressing intuitive questions of the type: How does a machine learn a new concept on the basis of examples? How can a neural network, after sufficient training, correctly predict the output of a previously unseen input? How much training is required to achieve a specified level of accuracy in the prediction? How can one "identify" the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite interval of time? This is the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory. The treatment of both topics side by side leads to new insights, as well as new results in both topics. An extensive references section and open problems will help readers to develop their own work in the field.
Author: Mathukumalli Vidyasagar
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 408
Get Book Here
Book Description
A Theory of Learning and Generalization provides a formal mathematical theory for addressing intuitive questions of the type: How does a machine learn a new concept on the basis of examples? How can a neural network, after sufficient training, correctly predict the output of a previously unseen input? How much training is required to achieve a specified level of accuracy in the prediction? How can one "identify" the dynamical behaviour of a nonlinear control system by observing its input-output behaviour over a finite interval of time? This is the first book to treat the problem of machine learning in conjunction with the theory of empirical processes, the latter being a well-established branch of probability theory. The treatment of both topics side by side leads to new insights, as well as new results in both topics. An extensive references section and open problems will help readers to develop their own work in the field.
Author: Mathukumalli Vidyasagar
Publisher: Springer Science & Business Media
ISBN: 1447137485
Category : Technology & Engineering
Languages : en
Pages : 498
Get Book Here
Book Description
How does a machine learn a new concept on the basis of examples? This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to learning of neural networks.
Author: Vladimir Vapnik
Publisher: Springer Science & Business Media
ISBN: 1475732643
Category : Mathematics
Languages : en
Pages : 324
Get Book Here
Book Description
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. This second edition contains three new chapters devoted to further development of the learning theory and SVM techniques. Written in a readable and concise style, the book is intended for statisticians, mathematicians, physicists, and computer scientists.
Author: Daniel A. Roberts
Publisher: Cambridge University Press
ISBN: 1316519333
Category : Computers
Languages : en
Pages : 473
Get Book Here
Book Description
This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Author: Marie T. Banich
Publisher: Psychology Press
ISBN: 1136945466
Category : Education
Languages : en
Pages : 380
Get Book Here
Book Description
This volume takes a multidisciplinary perspective on generalization of knowledge from several fields associated with Cognitive Science, including Cognitive Neuroscience, Computer Science, Education, Linguistics, Developmental Science, and Speech, Language and Hearing Sciences. The aim is to derive general principles from triangulation across different disciplines and approaches.
Author: Changfeng Wang
Publisher:
ISBN:
Category :
Languages : en
Pages : 292
Get Book Here
Book Description
Author: David. H Wolpert
Publisher: CRC Press
ISBN: 0429972156
Category : Mathematics
Languages : en
Pages : 311
Get Book Here
Book Description
This book provides different mathematical frameworks for addressing supervised learning. It is based on a workshop held under the auspices of the Center for Nonlinear Studies at Los Alamos and the Santa Fe Institute in the summer of 1992.
Author: Eytan Domany
Publisher: Springer Science & Business Media
ISBN: 1461207231
Category : Science
Languages : en
Pages : 322
Get Book Here
Book Description
One of the most challenging and fascinating problems of the theory of neural nets is that of asymptotic behavior, of how a system behaves as time proceeds. This is of particular relevance to many practical applications. Here we focus on association, generalization, and representation. We turn to the last topic first. The introductory chapter, "Global Analysis of Recurrent Neural Net works," by Andreas Herz presents an in-depth analysis of how to construct a Lyapunov function for various types of dynamics and neural coding. It includes a review of the recent work with John Hopfield on integrate-and fire neurons with local interactions. The chapter, "Receptive Fields and Maps in the Visual Cortex: Models of Ocular Dominance and Orientation Columns" by Ken Miller, explains how the primary visual cortex may asymptotically gain its specific structure through a self-organization process based on Hebbian learning. His argu ment since has been shown to be rather susceptible to generalization.
Author: Jennifer Walinga
Publisher: Hasanraza Ansari
ISBN:
Category : Body, Mind & Spirit
Languages : en
Pages : 810
Get Book Here
Book Description
This book is designed to help students organize their thinking about psychology at a conceptual level. The focus on behaviour and empiricism has produced a text that is better organized, has fewer chapters, and is somewhat shorter than many of the leading books. The beginning of each section includes learning objectives; throughout the body of each section are key terms in bold followed by their definitions in italics; key takeaways, and exercises and critical thinking activities end each section.
Author: Inbal Arnon
Publisher: John Benjamins Publishing
ISBN: 9027285047
Category : Language Arts & Disciplines
Languages : en
Pages : 312
Get Book Here
Book Description
Are all children exposed to the same linguistic input, and do they follow the same route in acquisition? The answer is no: The language that children hear differs even within a social class or cultural setting, as do the paths individual children take. The linguistic signal itself is also variable, both within and across speakers - the same sound is different across words; the same speech act can be realized with different constructions. The challenge here is to explain, given their diversity of experience, how children arrive at similar generalizations about their first language. This volume brings together studies of phonology, morphology, and syntax in development, to present a new perspective on how experience and variation shape children's linguistic generalizations. The papers deal with variation in forms, learning processes, and speaker features, and assess the impact of variation on the mechanisms and outcomes of language learning.
