The Resource Learning theory : 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings, Nader H. Bshouty, Claudio Gentile (eds.), (electronic resource)

Learning theory : 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings, Nader H. Bshouty, Claudio Gentile (eds.), (electronic resource)

Label
Learning theory : 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings
Title
Learning theory
Title remainder
20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings
Statement of responsibility
Nader H. Bshouty, Claudio Gentile (eds.)
Title variation
  • 20th Annual Conference on Learning Theory
  • Twentieth Annual Conference on Learning Theory
  • Conference on Learning Theory
  • COLT 2007
Creator
Contributor
Provider
Subject
Genre
Language
eng
Summary
This book constitutes the refereed proceedings of the 20th Annual Conference on Learning Theory, COLT 2007, held in San Diego, CA, USA in June 2007. The 41 revised full papers presented together with 5 articles on open problems and 2 invited lectures were carefully reviewed and selected from a total of 92 submissions. The papers cover a wide range of topics and are organized in topical sections on unsupervised, semisupervised and active learning, statistical learning theory, inductive inference, regularized learning, kernel methods, SVM, online and reinforcement learning, learning algorithms and limitations on learning, dimensionality reduction, other approaches, and open problems
Member of
Cataloging source
GW5XE
Image bit depth
0
LC call number
Q325.5
LC item number
.C66 2007eb
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2007
http://bibfra.me/vocab/lite/meetingName
Conference on Learning Theory
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • SpringerLink
  • Bshouty, Nader H
  • Gentile, Claudio
Series statement
Lecture Notes in Computer Science,
Series volume
4539
http://library.link/vocab/subjectName
  • Machine learning
  • COMPUTERS
  • COMPUTERS
  • Machine learning
  • Informatique
Label
Learning theory : 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings, Nader H. Bshouty, Claudio Gentile (eds.), (electronic resource)
Instantiates
Publication
Antecedent source
mixed
Bibliography note
Includes bibliographical references and index
Color
not applicable
Contents
Invited Presentations -- Property Testing: A Learning Theory Perspective -- Spectral Algorithms for Learning and Clustering -- Unsupervised, Semisupervised and Active Learning I -- Minimax Bounds for Active Learning -- Stability of k-Means Clustering -- Margin Based Active Learning -- Unsupervised, Semisupervised and Active Learning II -- Learning Large-Alphabet and Analog Circuits with Value Injection Queries -- Teaching Dimension and the Complexity of Active Learning -- Multi-view Regression Via Canonical Correlation Analysis -- Statistical Learning Theory -- Aggregation by Exponential Weighting and Sharp Oracle Inequalities -- Occam’s Hammer -- Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector -- Suboptimality of Penalized Empirical Risk Minimization in Classification -- Transductive Rademacher Complexity and Its Applications -- Inductive Inference -- U-Shaped, Iterative, and Iterative-with-Counter Learning -- Mind Change Optimal Learning of Bayes Net Structure -- Learning Correction Grammars -- Mitotic Classes -- Online and Reinforcement Learning I -- Regret to the Best vs. Regret to the Average -- Strategies for Prediction Under Imperfect Monitoring -- Bounded Parameter Markov Decision Processes with Average Reward Criterion -- Online and Reinforcement Learning II -- On-Line Estimation with the Multivariate Gaussian Distribution -- Generalised Entropy and Asymptotic Complexities of Languages -- Q-Learning with Linear Function Approximation -- Regularized Learning, Kernel Methods, SVM -- How Good Is a Kernel When Used as a Similarity Measure? -- Gaps in Support Vector Optimization -- Learning Languages with Rational Kernels -- Generalized SMO-Style Decomposition Algorithms -- Learning Algorithms and Limitations on Learning -- Learning Nested Halfspaces and Uphill Decision Trees -- An Efficient Re-scaled Perceptron Algorithm for Conic Systems -- A Lower Bound for Agnostically Learning Disjunctions -- Sketching Information Divergences -- Competing with Stationary Prediction Strategies -- Online and Reinforcement Learning III -- Improved Rates for the Stochastic Continuum-Armed Bandit Problem -- Learning Permutations with Exponential Weights -- Online and Reinforcement Learning IV -- Multitask Learning with Expert Advice -- Online Learning with Prior Knowledge -- Dimensionality Reduction -- Nonlinear Estimators and Tail Bounds for Dimension Reduction in l 1 Using Cauchy Random Projections -- Sparse Density Estimation with ?1 Penalties -- ?1 Regularization in Infinite Dimensional Feature Spaces -- Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking -- Other Approaches -- Observational Learning in Random Networks -- The Loss Rank Principle for Model Selection -- Robust Reductions from Ranking to Classification -- Open Problems -- Rademacher Margin Complexity -- Open Problems in Efficient Semi-supervised PAC Learning -- Resource-Bounded Information Gathering for Correlation Clustering -- Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation? -- When Is There a Free Matrix Lunch?
Dimensions
unknown
Extent
1 online resource (xii, 634 p.)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783540729273
Level of compression
uncompressed
Other physical details
ill.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
Stock number
978-3-540-72925-9
System control number
  • (OCoLC)184984904
  • (OCoLC)ocn184984904
Label
Learning theory : 20th Annual Conference on Learning Theory, COLT 2007, San Diego, CA, USA, June 13-15, 2007 : proceedings, Nader H. Bshouty, Claudio Gentile (eds.), (electronic resource)
Publication
Antecedent source
mixed
Bibliography note
Includes bibliographical references and index
Color
not applicable
Contents
Invited Presentations -- Property Testing: A Learning Theory Perspective -- Spectral Algorithms for Learning and Clustering -- Unsupervised, Semisupervised and Active Learning I -- Minimax Bounds for Active Learning -- Stability of k-Means Clustering -- Margin Based Active Learning -- Unsupervised, Semisupervised and Active Learning II -- Learning Large-Alphabet and Analog Circuits with Value Injection Queries -- Teaching Dimension and the Complexity of Active Learning -- Multi-view Regression Via Canonical Correlation Analysis -- Statistical Learning Theory -- Aggregation by Exponential Weighting and Sharp Oracle Inequalities -- Occam’s Hammer -- Resampling-Based Confidence Regions and Multiple Tests for a Correlated Random Vector -- Suboptimality of Penalized Empirical Risk Minimization in Classification -- Transductive Rademacher Complexity and Its Applications -- Inductive Inference -- U-Shaped, Iterative, and Iterative-with-Counter Learning -- Mind Change Optimal Learning of Bayes Net Structure -- Learning Correction Grammars -- Mitotic Classes -- Online and Reinforcement Learning I -- Regret to the Best vs. Regret to the Average -- Strategies for Prediction Under Imperfect Monitoring -- Bounded Parameter Markov Decision Processes with Average Reward Criterion -- Online and Reinforcement Learning II -- On-Line Estimation with the Multivariate Gaussian Distribution -- Generalised Entropy and Asymptotic Complexities of Languages -- Q-Learning with Linear Function Approximation -- Regularized Learning, Kernel Methods, SVM -- How Good Is a Kernel When Used as a Similarity Measure? -- Gaps in Support Vector Optimization -- Learning Languages with Rational Kernels -- Generalized SMO-Style Decomposition Algorithms -- Learning Algorithms and Limitations on Learning -- Learning Nested Halfspaces and Uphill Decision Trees -- An Efficient Re-scaled Perceptron Algorithm for Conic Systems -- A Lower Bound for Agnostically Learning Disjunctions -- Sketching Information Divergences -- Competing with Stationary Prediction Strategies -- Online and Reinforcement Learning III -- Improved Rates for the Stochastic Continuum-Armed Bandit Problem -- Learning Permutations with Exponential Weights -- Online and Reinforcement Learning IV -- Multitask Learning with Expert Advice -- Online Learning with Prior Knowledge -- Dimensionality Reduction -- Nonlinear Estimators and Tail Bounds for Dimension Reduction in l 1 Using Cauchy Random Projections -- Sparse Density Estimation with ?1 Penalties -- ?1 Regularization in Infinite Dimensional Feature Spaces -- Prediction by Categorical Features: Generalization Properties and Application to Feature Ranking -- Other Approaches -- Observational Learning in Random Networks -- The Loss Rank Principle for Model Selection -- Robust Reductions from Ranking to Classification -- Open Problems -- Rademacher Margin Complexity -- Open Problems in Efficient Semi-supervised PAC Learning -- Resource-Bounded Information Gathering for Correlation Clustering -- Are There Local Maxima in the Infinite-Sample Likelihood of Gaussian Mixture Estimation? -- When Is There a Free Matrix Lunch?
Dimensions
unknown
Extent
1 online resource (xii, 634 p.)
File format
multiple file formats
Form of item
  • online
  • electronic
Isbn
9783540729273
Level of compression
uncompressed
Other physical details
ill.
Quality assurance targets
absent
Reformatting quality
access
Specific material designation
remote
Stock number
978-3-540-72925-9
System control number
  • (OCoLC)184984904
  • (OCoLC)ocn184984904

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