Algorithmic Learning Theory: 24th International Conference, ALT 2013, Singapore, October 6-9, 2013, Proceedings: Lecture Notes in Computer Science, cartea 8139
Editat de Sanjay Jain, Rémi Munos, Frank Stephan, Thomas Zeugmannen Limba Engleză Paperback – 11 sep 2013
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Specificații
ISBN-13: 9783642409349
ISBN-10: 3642409342
Pagini: 416
Ilustrații: XVIII, 397 p. 30 illus.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.63 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642409342
Pagini: 416
Ilustrații: XVIII, 397 p. 30 illus.
Dimensiuni: 155 x 235 x 22 mm
Greutate: 0.63 kg
Ediția:2013
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
Public țintă
ResearchCuprins
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.
Caracteristici
Conference proceedings of the International Conference on Algorithmic Learning Theory