Algorithmic Learning Theory: 21st International Conference, ALT 2010, Canberra, Australia, October 6-8, 2010. Proceedings: Lecture Notes in Computer Science, cartea 6331
Editat de Marcus Hutter, Frank Stephan, Vladimir Vovk, Thomas Zeugmannen Limba Engleză Paperback – 27 sep 2010
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Specificații
ISBN-13: 9783642161070
ISBN-10: 3642161073
Pagini: 434
Ilustrații: XIII, 421 p. 45 illus.
Greutate: 0.64 kg
Ediția:2010
Editura: Springer Berlin, Heidelberg
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence
Locul publicării:Berlin, Heidelberg, Germany
ISBN-10: 3642161073
Pagini: 434
Ilustrații: XIII, 421 p. 45 illus.
Greutate: 0.64 kg
Ediția:2010
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.- 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 KernelLearning: Algorithms and Mistake Bounds.- An Identity for Kernel Ridge Regression.
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