Algorithmic Learning Theory 20th International Conference, ALT 2009, Porto, Portugal, October 3-5, 2009. Proceedings /

• Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
• Άλλοι συγγραφείς: Gavaldà, Ricard (Επιμελητής έκδοσης), Lugosi, Gábor (Επιμελητής έκδοσης), Zeugmann, Thomas (Επιμελητής έκδοσης), Zilles, Sandra (Επιμελητής έκδοσης)
• Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
• Γλώσσα: English
• Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2009.
• Σειρά: Lecture Notes in Computer Science, 5809
• Θέματα: Computer science.; Computer programming.; Data mining.; Information storage and retrieval.; Artificial intelligence.; Computational linguistics.; Pattern recognition.; Computer Science.; Artificial Intelligence (incl. Robotics).; Programming Techniques.; Data Mining and Knowledge Discovery.; Language Translation and Linguistics.; Pattern Recognition.; Information Storage and Retrieval.

This book constitutes the refereed proceedings of the 20th International Conference on Algorithmic Learning Theory, ALT 2009, held in Porto, Portugal, in October 2009, co-located with the 12th International Conference on Discovery Science, DS 2009. The 26 revised full papers presented together with...

Πίνακας περιεχομένων:

• Invited Papers
• The Two Faces of Active Learning
• Inference and Learning in Planning
• Mining Heterogeneous Information Networks by Exploring the Power of Links
• Learning and Domain Adaptation
• Learning on the Web
• Regular Contributions
• Prediction with Expert Evaluators’ Advice
• Pure Exploration in Multi-armed Bandits Problems
• The Follow Perturbed Leader Algorithm Protected from Unbounded One-Step Losses
• Computable Bayesian Compression for Uniformly Discretizable Statistical Models
• Calibration and Internal No-Regret with Random Signals
• St. Petersburg Portfolio Games
• Reconstructing Weighted Graphs with Minimal Query Complexity
• Learning Unknown Graphs
• Completing Networks Using Observed Data
• Average-Case Active Learning with Costs
• Canonical Horn Representations and Query Learning
• Learning Finite Automata Using Label Queries
• Characterizing Statistical Query Learning: Simplified Notions and Proofs
• An Algebraic Perspective on Boolean Function Learning
• Adaptive Estimation of the Optimal ROC Curve and a Bipartite Ranking Algorithm
• Complexity versus Agreement for Many Views
• Error-Correcting Tournaments
• Difficulties in Forcing Fairness of Polynomial Time Inductive Inference
• Learning Mildly Context-Sensitive Languages with Multidimensional Substitutability from Positive Data
• Uncountable Automatic Classes and Learning
• Iterative Learning from Texts and Counterexamples Using Additional Information
• Incremental Learning with Ordinal Bounded Example Memory
• Learning from Streams
• Smart PAC-Learners
• Approximation Algorithms for Tensor Clustering
• Agnostic Clustering.