Computational Learning Theory: 4th European Conference, EuroCOLT’99 Nordkirchen, Germany, March 29–31, 1999 Proceedings

Invited Lectures -- Theoretical Views of Boosting -- Open Theoretical Questions in Reinforcement Learning -- Learning from Random Examples -- A Geometric Approach to Leveraging Weak Learners -- Query by Committee, Linear Separation and Random Walks -- Hardness Results for Neural Network Approximatio...

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Bibliographic Details
Main Author: Fischer, Paul (Author)
Other Authors: Simon, Hans Ulrich (Other)
Format: Conference Paper
Language:English
Published: Berlin, Heidelberg Springer-Verlag Berlin Heidelberg 1999
Series:Lecture notes in computer science 1572
In: Lecture notes in computer science (1572)

Volumes / Articles: Show Volumes / Articles.
DOI:10.1007/3-540-49097-3
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Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/3-540-49097-3
Resolving-System, Volltext: http://dx.doi.org/10.1007/3-540-49097-3
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Author Notes:edited by Paul Fischer, Hans Ulrich Simon
Description
Summary:Invited Lectures -- Theoretical Views of Boosting -- Open Theoretical Questions in Reinforcement Learning -- Learning from Random Examples -- A Geometric Approach to Leveraging Weak Learners -- Query by Committee, Linear Separation and Random Walks -- Hardness Results for Neural Network Approximation Problems -- Learning from Queries and Counterexamples -- Learnability of Quantified Formulas -- Learning Multiplicity Automata from Smallest Counterexamples -- Exact Learning when Irrelevant Variables Abound -- An Application of Codes to Attribute-Efficient Learning -- Learning Range Restricted Horn Expressions -- Reinforcement Learning -- On the Asymptotic Behavior of a Constant Stepsize Temporal-Difference Learning Algorithm -- On-line Learning and Expert Advice -- Direct and Indirect Algorithms for On-line Learning of Disjunctions -- Averaging Expert Predictions -- Teaching and Learning -- On Teaching and Learning Intersection-Closed Concept Classes -- Inductive Inference -- Avoiding Coding Tricks by Hyperrobust Learning -- Mind Change Complexity of Learning Logic Programs -- Statistical Theory of Learning and Pattern Recognition -- Regularized Principal Manifolds -- Distribution-Dependent Vapnik-Chervonenkis Bounds -- Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition -- On Error Estimation for the Partitioning Classification Rule -- Margin Distribution Bounds on Generalization -- Generalization Performance of Classifiers in Terms of Observed Covering Numbers -- Entropy Numbers, Operators and Support Vector Kernels.
Item Description:Literaturangaben
Physical Description:Online Resource
ISBN:9783540490975
DOI:10.1007/3-540-49097-3