Vor Ort
Merkzettel Warenkorb
  • Produktbild: Algorithmic Learning Theory
  • Produktbild: Algorithmic Learning Theory

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

Aus der Reihe Lecture Notes in Artificial Intelligence

51,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

29.09.2008

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

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

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • 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.