Semi-supervised learning /

Saved in:
Bibliographic Details
Imprint:Cambridge, Mass. : MIT Press, ©2006.
Description:1 online resource (x, 508 pages) : illustrations
Language:English
Series:Adaptive computation and machine learning
Adaptive computation and machine learning.
Subject:
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11148728
Hidden Bibliographic Details
Other authors / contributors:Chapelle, Olivier.
Schölkopf, Bernhard.
Zien, Alexander.
ISBN:9780262255899
0262255898
0262033585
9780262033589
1282096184
9781282096189
1429414081
9781429414081
Digital file characteristics:data file
Notes:Includes bibliographical references (pages 479-497).
English.
Print version record.
Summary:A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at state-of-the-art algorithms, applications benchmark experiments, and directions for future research.
Other form:Print version: Semi-supervised learning. Cambridge, Mass. : MIT Press, ©2006 0262033585

MARC

LEADER 00000cam a22000004a 4500
001 11148728
005 20210426223940.7
006 m o d
007 cr cnu---unuuu
008 061129s2006 maua ob 000 0 eng d
019 |a 144221750  |a 182530233  |a 473855448  |a 482338380  |a 648224249  |a 698448592  |a 815786484  |a 888487196  |a 961552592  |a 962681986  |a 966247738  |a 988479849  |a 991907509  |a 992079045  |a 1011926238  |a 1037506878  |a 1037915633  |a 1038619749  |a 1055357085  |a 1062909239  |a 1081229069  |a 1083554933  |a 1102553906  |a 1125509500  |a 1130046352 
020 |a 9780262255899  |q (electronic bk.) 
020 |a 0262255898  |q (electronic bk.) 
020 |a 0262033585  |q (alk. paper) 
020 |a 9780262033589  |q (alk. paper) 
020 |a 1282096184 
020 |a 9781282096189 
020 |a 1429414081 
020 |a 9781429414081 
035 |a (OCoLC)76824411  |z (OCoLC)144221750  |z (OCoLC)182530233  |z (OCoLC)473855448  |z (OCoLC)482338380  |z (OCoLC)648224249  |z (OCoLC)698448592  |z (OCoLC)815786484  |z (OCoLC)888487196  |z (OCoLC)961552592  |z (OCoLC)962681986  |z (OCoLC)966247738  |z (OCoLC)988479849  |z (OCoLC)991907509  |z (OCoLC)992079045  |z (OCoLC)1011926238  |z (OCoLC)1037506878  |z (OCoLC)1037915633  |z (OCoLC)1038619749  |z (OCoLC)1055357085  |z (OCoLC)1062909239  |z (OCoLC)1081229069  |z (OCoLC)1083554933  |z (OCoLC)1102553906  |z (OCoLC)1125509500  |z (OCoLC)1130046352 
035 9 |a (OCLCCM-CC)76824411 
037 |a 6173  |b MIT Press 
037 |a 9780262255899  |b MIT Press 
040 |a N$T  |b eng  |e pn  |c N$T  |d YDXCP  |d OCLCQ  |d TEX  |d OCLCQ  |d N$T  |d IDEBK  |d OCLCQ  |d IEEEE  |d OCLCF  |d OTZ  |d NLGGC  |d OCLCQ  |d COCUF  |d E7B  |d DKDLA  |d OCLCQ  |d EBLCP  |d OCLCQ  |d AZK  |d LOA  |d UKOUP  |d JBG  |d DEBSZ  |d AGLDB  |d OCLCQ  |d MOR  |d PIFAG  |d PIFBR  |d ZCU  |d OCLCQ  |d MERUC  |d OCLCQ  |d NJR  |d WY@  |d U3W  |d OCLCQ  |d LUE  |d BRL  |d STF  |d WRM  |d OCLCQ  |d VTS  |d MERER  |d OCLCQ  |d ICG  |d VT2  |d AU@  |d OCLCQ  |d WYU  |d MITPR  |d A6Q  |d LEAUB  |d DKC  |d OCLCQ  |d OL$  |d OCLCQ  |d K6U  |d SFB  |d UKAHL 
049 |a MAIN 
050 4 |a Q325.75  |b .S42 2006eb 
072 7 |a COM  |x 005030  |2 bisacsh 
072 7 |a COM  |x 004000  |2 bisacsh 
072 7 |a K  |2 bicssc 
245 0 0 |a Semi-supervised learning /  |c [edited by] Olivier Chapelle, Bernhard Schölkopf, Alexander Zien. 
260 |a Cambridge, Mass. :  |b MIT Press,  |c ©2006. 
300 |a 1 online resource (x, 508 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a data file  |2 rda 
490 1 |a Adaptive computation and machine learning 
504 |a Includes bibliographical references (pages 479-497). 
588 0 |a Print version record. 
520 8 |a A comprehensive review of an area of machine learning that deals with the use of unlabeled data in classification problems, this text looks at state-of-the-art algorithms, applications benchmark experiments, and directions for future research. 
505 0 |a Series Foreword; Preface; 1 -- Introduction to Semi-Supervised Learning; 2 -- A Taxonomy for Semi-Supervised Learning Methods; 3 -- Semi-Supervised Text Classification Using EM; 4 -- Risks of Semi-Supervised Learning: How Unlabeled Data Can Degrade Performance of Generative Classifiers; 5 -- Probabilistic Semi-Supervised Clustering with Constraints; 6 -- Transductive Support Vector Machines; 7 -- Semi-Supervised Learning Using Semi- Definite Programming; 8 -- Gaussian Processes and the Null-Category Noise Model; 9 -- Entropy Regularization; 10 -- Data-Dependent Regularization. 
505 8 |a 11 -- Label Propagation and Quadratic Criterion12 -- The Geometric Basis of Semi-Supervised Learning; 13 -- Discrete Regularization; 14 -- Semi-Supervised Learning with Conditional Harmonic Mixing; 15 -- Graph Kernels by Spectral Transforms; 16- Spectral Methods for Dimensionality Reduction; 17 -- Modifying Distances; 18 -- Large-Scale Algorithms; 19 -- Semi-Supervised Protein Classification Using Cluster Kernels; 20 -- Prediction of Protein Function from Networks; 21 -- Analysis of Benchmarks; 22 -- An Augmented PAC Model for Semi- Supervised Learning. 
505 8 |a 23 -- Metric-Based Approaches for Semi- Supervised Regression and Classification24 -- Transductive Inference and Semi-Supervised Learning; 25 -- A Discussion of Semi-Supervised Learning and Transduction; References; Notation and Symbols; Contributors; Index. 
546 |a English. 
650 0 |a Supervised learning (Machine learning)  |0 http://id.loc.gov/authorities/subjects/sh94008290 
650 7 |a COMPUTERS  |x Enterprise Applications  |x Business Intelligence Tools.  |2 bisacsh 
650 7 |a COMPUTERS  |x Intelligence (AI) & Semantics.  |2 bisacsh 
650 7 |a Supervised learning (Machine learning)  |2 fast  |0 (OCoLC)fst01139041 
653 |a COMPUTER SCIENCE/Machine Learning & Neural Networks 
655 0 |a Electronic books. 
655 4 |a Electronic books. 
700 1 |a Chapelle, Olivier. 
700 1 |a Schölkopf, Bernhard. 
700 1 |a Zien, Alexander. 
776 0 8 |i Print version:  |t Semi-supervised learning.  |d Cambridge, Mass. : MIT Press, ©2006  |z 0262033585  |w (DLC) 2006044448  |w (OCoLC)64898359 
830 0 |a Adaptive computation and machine learning.  |0 http://id.loc.gov/authorities/names/n97066095 
903 |a HeVa 
929 |a oclccm 
999 f f |i 452cb354-8343-5b7e-8d79-4b41ecf5d426  |s 0214c626-468e-5475-869a-e581628f409a 
928 |t Library of Congress classification  |a Q325.75 .S42 2006eb  |l Online  |c UC-FullText  |u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=e000xna&AN=170037  |z eBooks on EBSCOhost  |g ebooks  |i 12236435