Advanced Lectures on Machine Learning (Record no. 187651)

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001 - CONTROL NUMBER
control field 978-3-540-36434-4
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423132428.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540364344
-- 978-3-540-36434-4
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/3-540-36434-X
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q334-342
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number TA347.A78
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source bicssc
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Subject category code COM004000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UYQ
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3
Edition number 23
245 10 - TITLE STATEMENT
Title Advanced Lectures on Machine Learning
Medium [electronic resource] :
Remainder of title Machine Learning Summer School 2002, Canberra, Australia, February 11-22, 2002, Revised Lectures /
Statement of responsibility, etc edited by Shahar Mendelson, Alexander J. Smola.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2003.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2003.
300 ## - PHYSICAL DESCRIPTION
Extent X, 266 p.
Other physical details online resource.
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-- online resource
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490 1# - SERIES STATEMENT
Series statement Lecture Notes in Artificial Intelligence,
International Standard Serial Number 2945-9141 ;
Volume number/sequential designation 2600
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note A Few Notes on Statistical Learning Theory -- A Short Introduction to Learning with Kernels -- Bayesian Kernel Methods -- An Introduction to Boosting and Leveraging -- An Introduction to Reinforcement Learning Theory: Value Function Methods -- Learning Comprehensible Theories from Structured Data -- Algorithms for Association Rules -- Online Learning of Linear Classifiers.
520 ## - SUMMARY, ETC.
Summary, etc Machine Learning has become a key enabling technology for many engineering applications and theoretical problems alike. To further discussions and to dis- minate new results, a Summer School was held on February 11–22, 2002 at the Australian National University. The current book contains a collection of the main talks held during those two weeks in February, presented as tutorial chapters on topics such as Boosting, Data Mining, Kernel Methods, Logic, Reinforcement Learning, and Statistical Learning Theory. The papers provide an in-depth overview of these exciting new areas, contain a large set of references, and thereby provide the interested reader with further information to start or to pursue his own research in these directions. Complementary to the book, a recorded video of the presentations during the Summer School can be obtained at http://mlg. anu. edu. au/summer2002 It is our hope that graduate students, lecturers, and researchers alike will ?nd this book useful in learning and teaching Machine Learning, thereby continuing the mission of the Summer School. Canberra, November 2002 Shahar Mendelson Alexander Smola Research School of Information Sciences and Engineering, The Australian National University Thanks and Acknowledgments We gratefully thank all the individuals and organizations responsible for the success of the workshop.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial intelligence.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Social sciences.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Humanities.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Artificial Intelligence.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Humanities and Social Sciences.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Theory of Computation.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Mendelson, Shahar.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Smola, Alexander J.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540005292
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783662180853
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Artificial Intelligence,
-- 2945-9141 ;
Volume number/sequential designation 2600
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/3-540-36434-X">https://doi.org/10.1007/3-540-36434-X</a>
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Koha item type eBooks-CSE-Springer

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