An introduction to artificial intelligence based on reproducing kernel Hilbert spaces / Sergei Pereverzyev.
Pereverzyev, Sergei, author.
2022
QA322.4
Available Online

Linked e-resources

Linked Resource Online Access
Concurrent users Unlimited
Authorized users Authorized users
Document Delivery Supplied Can lend chapters, not whole ebooks

Details

Title An introduction to artificial intelligence based on reproducing kernel Hilbert spaces / Sergei Pereverzyev.
Author Pereverzyev, Sergei, author.
ISBN 9783030983161 (electronic bk.)
3030983161 (electronic bk.)
9783030983154
3030983153
DOI https://doi.org/10.1007/978-3-030-98316-1
Published Cham : Birkhäuser, [2022]
Copyright ©2022
Language English
Description 1 online resource : illustrations (some color).
Other Standard Identifiers 10.1007/978-3-030-98316-1 doi
Call Number QA322.4
Dewey Decimal Classification 515/.733
Summary This textbook provides an in-depth exploration of statistical learning with reproducing kernels, an active area of research that can shed light on trends associated with deep neural networks. The author demonstrates how the concept of reproducing kernel Hilbert Spaces (RKHS), accompanied with tools from regularization theory, can be effectively used in the design and justification of kernel learning algorithms, which can address problems in several areas of artificial intelligence. Also provided is a detailed description of two biomedical applications of the considered algorithms, demonstrating how close the theory is to being practically implemented. Among the books several unique features is its analysis of a large class of algorithms of the Learning Theory that essentially comprise every linear regularization scheme, including Tikhonov regularization as a specific case. It also provides a methodology for analyzing not only different supervised learning problems, such as regression or ranking, but also different learning scenarios, such as unsupervised domain adaptation or reinforcement learning. By analyzing these topics using the same theoretical framework, rather than approaching them separately, their presentation is streamlined and made more approachable. An Introduction to Artificial Intelligence Based on Reproducing Kernel Hilbert Spaces is an ideal resource for graduate and postgraduate courses in computational mathematics and data science.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed June 2, 2022).
Series Compact textbooks in mathematics.
Available in Other Form Print version: 9783030983154
Linked Resources Online Access
Record Appears in Online Resources > Ebooks
All Resources
Introduction
Learning in Reproducing Kernel Hilbert Spaces and related integral operators
Selected topics of the regularization theory
Regularized learning in RKHS
Examples of Applications.

Browse Subjects

Show more subjects...

Statistics

from
to
Export