![](https://dblp.uni-trier.de/img/logo.ua.320x120.png)
![](https://dblp.uni-trier.de/img/dropdown.dark.16x16.png)
![](https://dblp.uni-trier.de/img/peace.dark.16x16.png)
Остановите войну!
for scientists:
![search dblp search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
![search dblp](https://dblp.uni-trier.de/img/search.dark.16x16.png)
default search action
4. EuroCOLT 1999: Nordkirchen, Germany
- Paul Fischer, Hans Ulrich Simon
:
Computational Learning Theory, 4th European Conference, EuroCOLT '99, Nordkirchen, Germany, March 29-31, 1999, Proceedings. Lecture Notes in Computer Science 1572, Springer 1999, ISBN 3-540-65701-0
Invited Lectures
- Robert E. Schapire:
Theoretical Views of Boosting. 1-10 - Richard S. Sutton:
Open Theoretical Questions in Reinforcement Learning. 11-17
Learning from Random Examples
- Nigel Duffy, David P. Helmbold:
A Geometric Approach to Leveraging Weak Learners. 18-33 - Ran Bachrach
, Shai Fine, Eli Shamir:
Query by Committee, Linear Separation and Random Walks. 34-49 - Peter L. Bartlett, Shai Ben-David:
Hardness Results for Neural Network Approximation Problems. 50-62
Learning from Queries and Counterexamples
- Víctor Dalmau, Peter Jeavons:
Learnability of Quantified Formulas. 63-78 - Jürgen Forster:
Learning Multiplicity Automata from Smallest Counterexamples. 79-90 - David Guijarro, Víctor Lavín, Vijay Raghavan:
Exact Learning when Irrelevant Variables Abound. 91-100 - Thomas Hofmeister:
An Application of Codes to Attribute-Efficient Learning. 101-110 - Roni Khardon:
Learning Range Restricted Horn Expressions. 111-125
Reinforcement Learning
- Vladislav Tadic:
On the Asymptotic Behaviour of a Constant Stepsize Temporal-Difference Learning Algorithm. 126-137
On-line Learning and Expert Advice
- David P. Helmbold, Sandra Panizza, Manfred K. Warmuth:
Direct and Indirect Algorithms for On-line Learning of Disjunctions. 138-152 - Jyrki Kivinen, Manfred K. Warmuth:
Averaging Expert Predictions. 153-167
Teaching and Learning
- Christian Kuhlmann:
On Teaching and Learning Intersection-Closed Concept Classes. 168-182
Inductive Inference
- Matthias Ott, Frank Stephan:
Avoiding Coding Tricks by Hyperrobust Learning. 183-197 - Sanjay Jain, Arun Sharma:
Mind Change Complexity of Learning Logic Programs. 198-213
Statistical Theory of Learning and Pattern Recognition
- Alexander J. Smola, Robert C. Williamson, Sebastian Mika, Bernhard Schölkopf:
Regularized Principal Manifolds. 214-229 - Nicolas Vayatis, Robert Azencott:
Distribution-Dependent Vapnik-Chervonenkis Bounds. 230-240 - András Antos:
Lower Bounds on the Rate of Convergence of Nonparametric Pattern Recognition. 241-252 - Márta Horváth:
On Error Estimation for the Partitioning Classification Rule. 253-262 - John Shawe-Taylor
, Nello Cristianini:
Margin Distribution Bounds on Generalization. 263-273 - John Shawe-Taylor
, Nello Cristianini:
Generalization Performance of Classifiers in Terms of Observed Covering Numbers. 274-284 - Robert C. Williamson, Alexander J. Smola, Bernhard Schölkopf:
Entropy Numbers, Operators and Support Vector Kernels. 285-299
![](https://dblp.uni-trier.de/img/cog.dark.24x24.png)
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.