Algorithmic Learning Theory 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings /

This volume contains the papers presented at the 21st International Conf- ence on Algorithmic Learning Theory (ALT 2010), which was held in Canberra, Australia, October 6-8, 2010. The conference was co-located with the 13th - ternational Conference on Discovery Science (DS 2010) and with the Machine...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Hutter, Marcus (Editor ), Stephan, Frank (Editor ), Vovk, Vladimir (Editor ), Zeugmann, Thomas (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Lecture Notes in Artificial Intelligence, 6331
Temas:
Artificial intelligence.
Computer programming.
Machine theory.
Algorithms.
Computer science.
Artificial Intelligence.
Programming Techniques.
Formal Languages and Automata Theory.
Theory of Computation.
Computer Science Logic and Foundations of Programming.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Editors' Introduction
  • Editors' Introduction
  • Invited Papers
  • Towards General Algorithms for Grammatical Inference
  • The Blessing and the Curse of the Multiplicative Updates
  • Discovery of Abstract Concepts by a Robot
  • Contrast Pattern Mining and Its Application for Building Robust Classifiers
  • Optimal Online Prediction in Adversarial Environments
  • Regular Contributions
  • An Algorithm for Iterative Selection of Blocks of Features
  • Bayesian Active Learning Using Arbitrary Binary Valued Queries
  • Approximation Stability and Boosting
  • A Spectral Approach for Probabilistic Grammatical Inference on Trees
  • PageRank Optimization in Polynomial Time by Stochastic Shortest Path Reformulation
  • Inferring Social Networks from Outbreaks
  • Distribution-Dependent PAC-Bayes Priors
  • PAC Learnability of a Concept Class under Non-atomic Measures: A Problem by Vidyasagar
  • A PAC-Bayes Bound for Tailored Density Estimation
  • Compressed Learning with Regular Concept
  • A Lower Bound for Learning Distributions Generated by Probabilistic Automata
  • Lower Bounds on Learning Random Structures with Statistical Queries
  • Recursive Teaching Dimension, Learning Complexity, and Maximum Classes
  • Toward a Classification of Finite Partial-Monitoring Games
  • Switching Investments
  • Prediction with Expert Advice under Discounted Loss
  • A Regularization Approach to Metrical Task Systems
  • Solutions to Open Questions for Non-U-Shaped Learning with Memory Limitations
  • Learning without Coding
  • Learning Figures with the Hausdorff Metric by Fractals
  • Inductive Inference of Languages from Samplings
  • Optimality Issues of Universal Greedy Agents with Static Priors
  • Consistency of Feature Markov Processes
  • Algorithms for Adversarial Bandit Problems with Multiple Plays
  • Online Multiple Kernel Learning: Algorithms and Mistake Bounds
  • An Identity for Kernel Ridge Regression.

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