The Resource Learning theory : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings, Peter Auer, Ron Meir (eds.), (electronic resource)

Learning theory : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings, Peter Auer, Ron Meir (eds.), (electronic resource)

Label
Learning theory : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings
Title
Learning theory
Title remainder
18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings
Statement of responsibility
Peter Auer, Ron Meir (eds.)
Title variation
  • 18th Annual Conference on Learning Theory
  • Eighteenth Annual Conference on Learning Theory
  • Conference on Learning Theory
  • COLT 2005
Creator
Contributor
Provider
Subject
Genre
Language
eng
Summary
This book constitutes the refereed proceedings of the 18th Annual Conference on Learning Theory, COLT 2005, held in Bertinoro, Italy in June 2005. The 45 revised full papers together with three articles on open problems presented were carefully reviewed and selected from a total of 120 submissions. The papers are organized in topical sections on: learning to rank, boosting, unlabeled data, multiclass classification, online learning, support vector machines, kernels and embeddings, inductive inference, unsupervised learning, generalization bounds, query learning, attribute efficiency, compression schemes, economics and game theory, separation results for learning models, and survey and prospects on open problems
Member of
Cataloging source
GW5XE
Image bit depth
0
LC call number
Q325.7
LC item number
.C68 2005eb
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2005
http://bibfra.me/vocab/lite/meetingName
Conference on Learning Theory
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorDate
1964-
http://library.link/vocab/relatedWorkOrContributorName
  • SpringerLink
  • Auer, Peter
  • Meir, Ron
Series statement
Lecture Notes in Computer Science,
Series volume
3559
http://library.link/vocab/subjectName
  • Computational learning theory
  • Machine learning
  • Artificial intelligence
  • Apprentissage informatique, Théorie de l'
  • Intelligence artificielle
  • Théorie de l'apprentissage informatique
  • Intelligence artificielle
  • Artificial intelligence
  • Computational learning theory
  • Machine learning
  • Informatique
Label
Learning theory : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings, Peter Auer, Ron Meir (eds.), (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Bibliography note
Includes bibliographical references and index
Color
not applicable
Contents
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 and Strong 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
Dimensions
unknown
Extent
1 online resource (xi, 692 p.)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783540265566
Level of compression
uncompressed
Other physical details
ill.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
Stock number
978-3-540-26556-6
System control number
  • (OCoLC)262681359
  • (OCoLC)ocn262681359
Label
Learning theory : 18th Annual Conference on Learning Theory, COLT 2005, Bertinoro, Italy, June 27-30, 2005 : proceedings, Peter Auer, Ron Meir (eds.), (electronic resource)
Publication
Antecedent source
mixed
Bibliography note
Includes bibliographical references and index
Color
not applicable
Contents
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 and Strong 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
Dimensions
unknown
Extent
1 online resource (xi, 692 p.)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783540265566
Level of compression
uncompressed
Other physical details
ill.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
Stock number
978-3-540-26556-6
System control number
  • (OCoLC)262681359
  • (OCoLC)ocn262681359

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