000 -LEADER |
fixed length control field |
04711nam a2200637 i 4500 |
001 - CONTROL NUMBER |
control field |
6813050 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
IEEE |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20200413152851.0 |
006 - FIXED-LENGTH DATA ELEMENTS--ADDITIONAL MATERIAL CHARACTERISTICS |
fixed length control field |
m||||eo||d|||||||| |
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
fixed length control field |
cr an |||m|||a |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
081101s2008 caua fob 000 0 eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781598296600 (electronic bk.) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781598296594 (pbk.) |
024 7# - OTHER STANDARD IDENTIFIER |
Standard number or code |
10.2200/S00130ED1V01Y200806AIM004 |
Source of number or code |
doi |
035 ## - SYSTEM CONTROL NUMBER |
System control number |
(OCoLC)235585411 |
035 ## - SYSTEM CONTROL NUMBER |
System control number |
(CaBNVSL)gtp00531511 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
CaBNVSL |
Transcribing agency |
CaBNVSL |
Modifying agency |
CaBNVSL |
050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
Q387 |
Item number |
.M247 2008 |
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
006.3/32 |
Edition number |
22 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Mahadevan, Sridhar, |
Dates associated with a name |
1960- |
245 10 - TITLE STATEMENT |
Title |
Representation discovery using harmonic analysis |
Medium |
[electronic resource] / |
Statement of responsibility, etc. |
Sridhar Mahadevan. |
250 ## - EDITION STATEMENT |
Edition statement |
1st ed. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. |
Place of publication, distribution, etc. |
San Rafael, Calif (1537 Fourth Street, San Rafael, CA 94901 USA) : |
Name of publisher, distributor, etc. |
Morgan & Claypool Publishers, |
Date of publication, distribution, etc. |
2008. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
1 electronic text (xii, 147 p. : ill.) : |
Other physical details |
digital file. |
490 1# - SERIES STATEMENT |
Series statement |
Synthesis lectures on artificial intelligence and machine learning, |
International Standard Serial Number |
1939-4616 ; |
Volume/sequential designation |
#4 |
538 ## - SYSTEM DETAILS NOTE |
System details note |
Mode of access: World Wide Web. |
538 ## - SYSTEM DETAILS NOTE |
System details note |
System requirements: Adobe Acrobat Reader. |
500 ## - GENERAL NOTE |
General note |
Part of: Synthesis digital library of engineering and computer science. |
500 ## - GENERAL NOTE |
General note |
Series from website. |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc. note |
Includes bibliographical references (p. 137-145). |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Overview -- Vector spaces -- Fourier bases on graphs -- Multiscale bases on graphs -- Scaling to large spaces -- Case study: State-space planning -- Case study: computer graphics -- Case study: natural language -- Future directions. |
506 1# - RESTRICTIONS ON ACCESS NOTE |
Terms governing access |
Abstract freely available; full-text restricted to subscribers or individual document purchasers. |
510 0# - CITATION/REFERENCES NOTE |
Name of source |
Compendex |
510 0# - CITATION/REFERENCES NOTE |
Name of source |
INSPEC |
510 0# - CITATION/REFERENCES NOTE |
Name of source |
Google scholar |
510 0# - CITATION/REFERENCES NOTE |
Name of source |
Google book search |
520 ## - SUMMARY, ETC. |
Summary, etc. |
Representations are at the heart of artificial intelligence (AI). This book is devoted to the problem of representation discovery: how can an intelligent system construct representations from its experience? Representation discovery re-parameterizes the state space - prior to the application of information retrieval, machine learning, or optimization techniques - facilitating later inference processes by constructing new task-specific bases adapted to the state space geometry. This book presents a general approach to representation discovery using the framework of harmonic analysis, in particular Fourier and wavelet analysis. Biometric compression methods, the compact disc, the computerized axial tomography (CAT) scanner in medicine, JPEG compression, and spectral analysis of time-series data are among the many applications of classical Fourier and wavelet analysis. A central goal of this book is to show that these analytical tools can be generalized from their usual setting in (infinite-dimensional) Euclidean spaces to discrete (finite-dimensional) spaces typically studied in many subfields of AI. Generalizing harmonic analysis to discrete spaces poses many challenges: a discrete representation of the space must be adaptively acquired; basis functions are not pre-defined, but rather must be constructed. Algorithms for efficiently computing and representing bases require dealing with the curse of dimensionality. However, the benefits can outweigh the costs, since the extracted basis functions outperform parametric bases as they often reflect the irregular shape of a particular state space. Case studies from computer graphics, information retrieval, machine learning, and state space planning are used to illustrate the benefits of the proposed framework, and the challenges that remain to be addressed. Representation discovery is an actively developing field, and the author hopes this book will encourage other researchers to explore this exciting area of research. |
530 ## - ADDITIONAL PHYSICAL FORM AVAILABLE NOTE |
Additional physical form available note |
Also available in print. |
588 ## - SOURCE OF DESCRIPTION NOTE |
Source of description note |
Title from PDF t.p. (viewed on Nov. 1, 2008). |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Knowledge representation (Information theory) |
General subdivision |
Mathematics. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Wavelets (Mathematics) |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name entry element |
Fourier analysis. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Artificial intelligence. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Dimensionality reduction. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Feature construction. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Harmonic analysis. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Image processing. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Information retrieval. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Linear algebra. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Machine learning. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
Natural language processing. |
690 ## - LOCAL SUBJECT ADDED ENTRY--TOPICAL TERM (OCLC, RLIN) |
Topical term or geographic name as entry element |
State space planning. |
730 0# - ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Synthesis digital library of engineering and computer science. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE |
Uniform title |
Synthesis lectures on artificial intelligence and machine learning ; |
Volume/sequential designation |
#4. |
856 42 - ELECTRONIC LOCATION AND ACCESS |
Materials specified |
Abstract with links to resource |
Uniform Resource Identifier |
http://ieeexplore.ieee.org/servlet/opac?bknumber=6813050 |