Learning Theory (Record no. 182420)

MARC details
000 -LEADER
fixed length control field 06264nam a22005895i 4500
001 - CONTROL NUMBER
control field 978-3-540-31892-7
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125844.0
007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION
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fixed length control field 100715s2005 gw | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783540318927
-- 978-3-540-31892-7
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/b137542
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
072 #7 - SUBJECT CATEGORY CODE
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 Learning Theory
Medium [electronic resource] :
Remainder of title 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005, Proceedings /
Statement of responsibility, etc edited by Peter Auer, Ron Meir.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2005.
264 #1 -
-- Berlin, Heidelberg :
-- Springer Berlin Heidelberg :
-- Imprint: Springer,
-- 2005.
300 ## - PHYSICAL DESCRIPTION
Extent XII, 692 p.
Other physical details online resource.
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-- computer
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-- online resource
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-- text file
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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 3559
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Learning to Rank -- Ranking and Scoring Using Empirical Risk Minimization -- Learnability of Bipartite Ranking Functions -- Stability and Generalization of Bipartite Ranking Algorithms -- Loss Bounds for Online Category Ranking -- Boosting -- Margin-Based Ranking Meets Boosting in the Middle -- Martingale Boosting -- The Value of Agreement, a New Boosting Algorithm -- Unlabeled Data, Multiclass Classification -- A PAC-Style Model for Learning from Labeled and Unlabeled Data -- Generalization Error Bounds Using Unlabeled Data -- On the Consistency of Multiclass Classification Methods -- Sensitive Error Correcting Output Codes -- Online Learning I -- Data Dependent Concentration Bounds for Sequential Prediction Algorithms -- The Weak Aggregating Algorithm and Weak Mixability -- Tracking the Best of Many Experts -- Improved Second-Order Bounds for Prediction with Expert Advice -- Online Learning II -- Competitive Collaborative Learning -- Analysis of Perceptron-Based Active Learning -- A New Perspective on an Old Perceptron Algorithm -- Support Vector Machines -- Fast Rates for Support Vector Machines -- Exponential Convergence Rates in Classification -- General Polynomial Time Decomposition Algorithms -- Kernels and Embeddings -- Approximating a Gram Matrix for Improved Kernel-Based Learning -- Learning Convex Combinations of Continuously Parameterized Basic Kernels -- On the Limitations of Embedding Methods -- Leaving the Span -- Inductive Inference -- Variations on U-Shaped Learning -- Mind Change Efficient Learning -- On a Syntactic Characterization of Classification with a Mind Change Bound -- Unsupervised Learning -- Ellipsoid Approximation Using Random Vectors -- The Spectral Method for General Mixture Models -- On Spectral Learning of Mixtures of Distributions -- From Graphs to Manifolds – Weak andStrong Pointwise Consistency of Graph Laplacians -- Towards a Theoretical Foundation for Laplacian-Based Manifold Methods -- Generalization Bounds -- Permutation Tests for Classification -- Localized Upper and Lower Bounds for Some Estimation Problems -- Improved Minimax Bounds on the Test and Training Distortion of Empirically Designed Vector Quantizers -- Rank, Trace-Norm and Max-Norm -- Query Learning, Attribute Efficiency, Compression Schemes -- Learning a Hidden Hypergraph -- On Attribute Efficient and Non-adaptive Learning of Parities and DNF Expressions -- Unlabeled Compression Schemes for Maximum Classes -- Economics and Game Theory -- Trading in Markovian Price Models -- From External to Internal Regret -- Separation Results for Learning Models -- Separating Models of Learning from Correlated and Uncorrelated Data -- Asymptotic Log-Loss of Prequential Maximum Likelihood Codes -- Teaching Classes with High Teaching Dimension Using Few Examples -- Open Problems -- Optimum Follow the Leader Algorithm -- The Cross Validation Problem -- Compute Inclusion Depth of a Pattern.
520 ## - SUMMARY, ETC.
Summary, etc This volume contains papers presented at the Eighteenth Annual Conference on Learning Theory (previously known as the Conference on Computational Learning Theory) held in Bertinoro, Italy from June 27 to 30, 2005. The technical program contained 45 papers selected from 120 submissions, 3 open problems selected from among 5 contributed, and 2 invited lectures. The invited lectures were given by Sergiu Hart on “Uncoupled Dynamics and Nash Equilibrium”, and by Satinder Singh on “Rethinking State, Action, and Reward in Reinforcement Learning”. These papers were not included in this volume. The Mark Fulk Award is presented annually for the best paper co-authored by a student. The student selected this year was Hadi Salmasian for the paper titled “The Spectral Method for General Mixture Models” co-authored with Ravindran Kannan and Santosh Vempala. The number of papers submitted to COLT this year was exceptionally high. In addition to the classical COLT topics, we found an increase in the number of submissions related to novel classi?cation scenarios such as ranking. This - crease re?ects a healthy shift towards more structured classi?cation problems, which are becoming increasingly relevant to practitioners.
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 Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine theory.
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 Theory of Computation.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Algorithms.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Formal Languages and Automata Theory.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Auer, Peter.
Relator term editor.
Relator code edt
-- http://id.loc.gov/vocabulary/relators/edt
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Meir, Ron.
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 9783540265566
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9783540812425
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Lecture Notes in Artificial Intelligence,
-- 2945-9141 ;
Volume number/sequential designation 3559
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/b137542">https://doi.org/10.1007/b137542</a>
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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