MARC details
| 000 -LEADER |
|---|
| fixed length control field |
04601nam a22005295i 4500 |
| 003 - CONTROL NUMBER IDENTIFIER |
|---|
| control field |
TR-AnTOB |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
|---|
| control field |
20231117181406.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION |
|---|
| fixed length control field |
cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
210831s2022 sz | s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783030743864 |
| 024 7# - OTHER STANDARD IDENTIFIER |
|---|
| Standard number or code |
10.1007/978-3-030-74386-4 |
| Source of number or code |
doi |
| 040 ## - CATALOGING SOURCE |
|---|
| Original cataloging agency |
TR-AnTOB |
| Language of cataloging |
eng |
| Transcribing agency |
TR-AnTOB |
| Description conventions |
rda |
| 041 ## - LANGUAGE CODE |
|---|
| Language code of text/sound track or separate title |
İngilizce |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER |
|---|
| Classification number |
TA347.T4 |
| 072 #7 - SUBJECT CATEGORY CODE |
|---|
| Subject category code |
TJFC |
| Source |
bicssc |
|
|---|
| Subject category code |
TEC008010 |
| Source |
bisacsh |
|
|---|
| Subject category code |
TJFC |
| Source |
thema |
| 090 ## - LOCALLY ASSIGNED LC-TYPE CALL NUMBER (OCLC); LOCAL CALL NUMBER (RLIN) |
|---|
| Classification number (OCLC) (R) ; Classification number, CALL (RLIN) (NR) |
TA347.T4EBK |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Liu, Yipeng. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 245 10 - TITLE STATEMENT |
|---|
| Title |
Tensor Computation for Data Analysis |
| Medium |
[electronic resource] / |
| Statement of responsibility, etc. |
by Yipeng Liu, Jiani Liu, Zhen Long, Ce Zhu. |
| 250 ## - EDITION STATEMENT |
|---|
| Edition statement |
1st ed. 2022. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
|---|
| Place of production, publication, distribution, manufacture |
Cham : |
| Name of producer, publisher, distributor, manufacturer |
Springer International Publishing : |
| -- |
Imprint: Springer, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2022. |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
1 online resource |
| 336 ## - CONTENT TYPE |
|---|
| Content type term |
text |
| Content type code |
txt |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
|---|
| Media type term |
computer |
| Media type code |
c |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
|---|
| Carrier type term |
online resource |
| Carrier type code |
cr |
| Source |
rdacarrier |
| 347 ## - DIGITAL FILE CHARACTERISTICS |
|---|
| File type |
text file |
| Encoding format |
PDF |
| Source |
rda |
| 505 0# - FORMATTED CONTENTS NOTE |
|---|
| Formatted contents note |
1- Tensor Computation -- 2-Tensor Decomposition -- 3-Tensor Dictionary Learning -- 4-Low Rank Tensor Recovery -- 5-Coupled Tensor for Data Analysis -- 6-Robust Principal Tensor Component Analysis -- 7-Tensor Regression -- 8-Statistical Tensor Classification -- 9-Tensor Subspace Cluster -- 10-Tensor Decomposition in Deep Networks -- 11-Deep Networks for Tensor Approximation -- 12-Tensor-based Gaussian Graphical Model -- 13-Tensor Sketch. . |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc. |
Tensor is a natural representation for multi-dimensional data, and tensor computation can avoid possible multi-linear data structure loss in classical matrix computation-based data analysis. This book is intended to provide non-specialists an overall understanding of tensor computation and its applications in data analysis, and benefits researchers, engineers, and students with theoretical, computational, technical and experimental details. It presents a systematic and up-to-date overview of tensor decompositions from the engineer's point of view, and comprehensive coverage of tensor computation based data analysis techniques. In addition, some practical examples in machine learning, signal processing, data mining, computer vision, remote sensing, and biomedical engineering are also presented for easy understanding and implementation. These data analysis techniques may be further applied in other applications on neuroscience, communication, psychometrics, chemometrics, biometrics, quantum physics, quantum chemistry, etc. The discussion begins with basic coverage of notations, preliminary operations in tensor computations, main tensor decompositions and their properties. Based on them, a series of tensor-based data analysis techniques are presented as the tensor extensions of their classical matrix counterparts, including tensor dictionary learning, low rank tensor recovery, tensor completion, coupled tensor analysis, robust principal tensor component analysis, tensor regression, logistical tensor regression, support tensor machine, multilinear discriminate analysis, tensor subspace clustering, tensor-based deep learning, tensor graphical model and tensor sketch. The discussion also includes a number of typical applications with experimental results, such as image reconstruction, image enhancement, data fusion, signal recovery, recommendation system, knowledge graph acquisition, traffic flow prediction, link prediction, environmental prediction, weather forecasting, background extraction, human pose estimation, cognitive state classification from fMRI, infrared small target detection, heterogeneous information networks clustering, multi-view image clustering, and deep neural network compression. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name entry element |
Electronic circuits. |
|
|---|
| Topical term or geographic name entry element |
Signal processing. |
|
|---|
| Topical term or geographic name entry element |
Cooperating objects (Computer systems). |
|
|---|
| Topical term or geographic name entry element |
Electronic Circuits and Systems. |
|
|---|
| Topical term or geographic name entry element |
Digital and Analog Signal Processing. |
|
|---|
| Topical term or geographic name entry element |
Cyber-Physical Systems. |
| 653 #0 - INDEX TERM--UNCONTROLLED |
|---|
| Uncontrolled term |
Calculus of tensors |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Liu, Jiani. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
|
|---|
| Personal name |
Long, Zhen. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
|
|---|
| Personal name |
Zhu, Ce. |
| Relator term |
author. |
| Relator code |
aut |
| -- |
http://id.loc.gov/vocabulary/relators/aut |
| 710 2# - ADDED ENTRY--CORPORATE NAME |
|---|
| Corporate name or jurisdiction name as entry element |
SpringerLink (Online service) |
| 856 40 - ELECTRONIC LOCATION AND ACCESS |
|---|
| Uniform Resource Identifier |
<a href="https://doi.org/10.1007/978-3-030-74386-4">https://doi.org/10.1007/978-3-030-74386-4</a> |
| Materials specified |
Springer eBooks |
| Public note |
Online access link to the resource |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
Library of Congress Classification |
| Koha item type |
E-Book |
