Geschäftskunden Kundenprogramme

KI-Beratung Beta
Vor Ort
Merkzettel Warenkorb
Produktbild: Algorithmic Learning Theory
Band 3244

Algorithmic Learning Theory 15th International Conference, ALT 2004, Padova, Italy, October 2-5, 2004. Proceedings

Aus der Reihe Lecture Notes in Artificial Intelligence

Fr. 73.90

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.09.2004

Abbildungen

XIV, 514 p.

Herausgeber

Shai Ben David + weitere

Verlag

Springer Berlin

Seitenzahl

514

Maße (L/B/H)

23.5/15.5/2.9 cm

Gewicht

791 g

Auflage

2004

Sprache

Englisch

ISBN

978-3-540-23356-5

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

23.09.2004

Abbildungen

XIV, 514 p.

Herausgeber

Verlag

Springer Berlin

Seitenzahl

514

Maße (L/B/H)

23.5/15.5/2.9 cm

Gewicht

791 g

Auflage

2004

Sprache

Englisch

ISBN

978-3-540-23356-5

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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
  • Invited Papers.- String Pattern Discovery.- Applications of Regularized Least Squares to Classification Problems.- Probabilistic Inductive Logic Programming.- Hidden Markov Modelling Techniques for Haplotype Analysis.- Learning, Logic, and Probability: A Unified View.- Regular Contributions.- Learning Languages from Positive Data and Negative Counterexamples.- Inductive Inference of Term Rewriting Systems from Positive Data.- On the Data Consumption Benefits of Accepting Increased Uncertainty.- Comparison of Query Learning and Gold-Style Learning in Dependence of the Hypothesis Space.- Learning r-of-k Functions by Boosting.- Boosting Based on Divide and Merge.- Learning Boolean Functions in AC 0 on Attribute and Classification Noise.- Decision Trees: More Theoretical Justification for Practical Algorithms.- Application of Classical Nonparametric Predictors to Learning Conditionally I.I.D. Data.- Complexity of Pattern Classes and Lipschitz Property.- On Kernels, Margins, and Low-Dimensional Mappings.- Estimation of the Data Region Using Extreme-Value Distributions.- Maximum Entropy Principle in Non-ordered Setting.- Universal Convergence of Semimeasures on Individual Random Sequences.- A Criterion for the Existence of Predictive Complexity for Binary Games.- Full Information Game with Gains and Losses.- Prediction with Expert Advice by Following the Perturbed Leader for General Weights.- On the Convergence Speed of MDL Predictions for Bernoulli Sequences.- Relative Loss Bounds and Polynomial-Time Predictions for the k-lms-net Algorithm.- On the Complexity of Working Set Selection.- Convergence of a Generalized Gradient Selection Approach for the Decomposition Method.- Newton Diagram and Stochastic Complexity in Mixture of Binomial Distributions.- Learnability of Relatively Quantified Generalized Formulas.- Learning Languages Generated by Elementary Formal Systems and Its Application to SH Languages.- New Revision Algorithms.- The Subsumption Lattice and Query Learning.- Learning of Ordered Tree Languages with Height-Bounded Variables Using Queries.- Learning Tree Languages from Positive Examples and Membership Queries.- Learning Content Sequencing in an Educational Environment According to Student Needs.- Tutorial Papers.- Statistical Learning in Digital Wireless Communications.- A BP-Based Algorithm for Performing Bayesian Inference in Large Perceptron-Type Networks.- Approximate Inference in Probabilistic Models.