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Algorithmic Learning Theory 24th International Conference, ALT 2013, Singapore, October 6-9, 2013, Proceedings /

This book constitutes the proceedings of the 24th International Conference on Algorithmic Learning Theory, ALT 2013, held in Singapore in October 2013, and co-located with the 16th International Conference on Discovery Science, DS 2013. The 23 papers presented in this volume were carefully reviewed...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Jain, Sanjay (Editor ), Munos, Rémi (Editor ), Stephan, Frank (Editor ), Zeugmann, Thomas (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2013.
Edición:1st ed. 2013.
Colección:Lecture Notes in Artificial Intelligence, 8139
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Editors' Introduction
  • Learning and Optimizing with Preferences
  • Efficient Algorithms for Combinatorial Online Prediction
  • Exact Learning from Membership Queries: Some Techniques, Results and New Directions
  • Online Learning Universal Algorithm for Trading in Stock Market Based on the Method of Calibration
  • Combinatorial Online Prediction via Metarounding
  • On Competitive Recommendations
  • Online PCA with Optimal Regrets
  • Inductive Inference and Grammatical Inference Partial Learning of Recursively Enumerable Languages
  • Topological Separations in Inductive Inference
  • PAC Learning of Some Subclasses of Context-Free Grammars with Basic Distributional Properties from Positive Data
  • Universal Knowledge-Seeking Agents for Stochastic Environments
  • Teaching and Learning from Queries Order Compression Schemes
  • Learning a Bounded-Degree Tree Using Separator Queries
  • Faster Hoeffding Racing: Bernstein Races via Jackknife Estimates
  • Robust Risk-Averse Stochastic Multi-armed Bandits
  • An Efficient Algorithm for Learning with Semi-bandit Feedback
  • Differentially-Private Learning of Low Dimensional Manifolds
  • Generalization and Robustness of Batched Weighted Average Algorithm with V-Geometrically Ergodic Markov Data
  • Adaptive Metric Dimensionality Reduction
  • Dimension-Adaptive Bounds on Compressive FLD Classification
  • Bayesian Methods for Low-Rank Matrix Estimation: Short Survey and Theoretical Study
  • Concentration and Confidence for Discrete Bayesian Sequence Predictors
  • Algorithmic Connections between Active Learning and Stochastic Convex Optimization
  • Unsupervised/Semi-Supervised Learning Unsupervised Model-Free Representation Learning
  • Fast Spectral Clustering via the Nyström Method
  • Nonparametric Multiple Change Point Estimation in Highly Dependent Time Series.