TY  - BOOK
AU  - Fischer,Paul
AU  - Simon,Hans Ulrich
ED  - SpringerLink (Online service)
TI  - Computational Learning Theory: 4th European Conference, EuroCOLT’99 Nordkirchen, Germany, March 29–31, 1999 Proceedings 
T2  - Lecture Notes in Computer Science,
SN  - 9783540490975
AV  - Q334-342 
U1  - 006.3 23
PY  - 1999///
CY  - Berlin, Heidelberg
PB  - Springer Berlin Heidelberg
KW  - Computer science
KW  - Computer software
KW  - Artificial intelligence
KW  - Computer Science
KW  - Artificial Intelligence (incl. Robotics)
KW  - Mathematical Logic and Formal Languages
KW  - Algorithm Analysis and Problem Complexity
KW  - Computation by Abstract Devices
N1  - 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
UR  - http://dx.doi.org/10.1007/3-540-49097-3
ER  -