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Algorithmic Learning Theory 19th International Conference, ALT 2008, Budapest, Hungary, October 13-16, 2008, Proceedings

Aus der Reihe Lecture Notes in Computer Science

49,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.09.2008

Abbildungen

XIII, 467 p.

Herausgeber

Yoav Freund + weitere

Verlag

Springer Berlin

Seitenzahl

467

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

727 g

Auflage

2008

Sprache

Englisch

ISBN

978-3-540-87986-2

Beschreibung

Portrait

Yoav Freund is Professor of Computer Science at the University of California, San Diego.

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.09.2008

Abbildungen

XIII, 467 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

467

Maße (L/B/H)

23,5/15,5/2,7 cm

Gewicht

727 g

Auflage

2008

Sprache

Englisch

ISBN

978-3-540-87986-2

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: GPSR Kontakt

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  • Produktbild: Algorithmic Learning Theory
  • Produktbild: Algorithmic Learning Theory
  • Invited Papers.- On Iterative Algorithms with an Information Geometry Background.- Visual Analytics: Combining Automated Discovery with Interactive Visualizations.- Some Mathematics behind Graph Property Testing.- Finding Total and Partial Orders from Data for Seriation.- Computational Models of Neural Representations in the Human Brain.- Regular Contributions.- Generalization Bounds for Some Ordinal Regression Algorithms.- Approximation of the Optimal ROC Curve and a Tree-Based Ranking Algorithm.- Sample Selection Bias Correction Theory.- Exploiting Cluster-Structure to Predict the Labeling of a Graph.- A Uniform Lower Error Bound for Half-Space Learning.- Generalization Bounds for K-Dimensional Coding Schemes in Hilbert Spaces.- Learning and Generalization with the Information Bottleneck.- Growth Optimal Investment with Transaction Costs.- Online Regret Bounds for Markov Decision Processes with Deterministic Transitions.- On-Line Probability, Complexity and Randomness.- Prequential Randomness.- Some Sufficient Conditions on an Arbitrary Class of Stochastic Processes for the Existence of a Predictor.- Nonparametric Independence Tests: Space Partitioning and Kernel Approaches.- Supermartingales in Prediction with Expert Advice.- Aggregating Algorithm for a Space of Analytic Functions.- Smooth Boosting for Margin-Based Ranking.- Learning with Continuous Experts Using Drifting Games.- Entropy Regularized LPBoost.- Optimally Learning Social Networks with Activations and Suppressions.- Active Learning in Multi-armed Bandits.- Query Learning and Certificates in Lattices.- Clustering with Interactive Feedback.- Active Learning of Group-Structured Environments.- Finding the Rare Cube.- Iterative Learning of Simple External Contextual Languages.- Topological Properties of Concept Spaces.- Dynamically Delayed Postdictive Completeness and Consistency in Learning.- Dynamic Modeling in Inductive Inference.- Optimal Language Learning.- Numberings Optimal for Learning.- Learning with Temporary Memory.- Erratum: Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors.