Algorithmic Learning Theory [[electronic resource] ] : 16th International Conference, ALT 2005, Singapore, October 8-11, 2005, Proceedings / / edited by Sanjay Jain, Hans Ulrich Simon, Etsuji Tomita

• Pubblicazione: Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2005
• Edizione: 1st ed. 2005.
• Descrizione fisica: 1 online resource (XII, 491 p.)
• Disciplina: 006.3
• Soggetto topico: Artificial intelligence; Computers; Algorithms; Mathematical logic; Natural language processing (Computer science); Artificial Intelligence; Computation by Abstract Devices; Algorithm Analysis and Problem Complexity; Mathematical Logic and Formal Languages; Natural Language Processing (NLP)
• Persona (resp. second.): JainSanjay; SimonHans Ulrich; TomitaEtsuji
• Note generali: Bibliographic Level Mode of Issuance: Monograph
• Nota di bibliografia: Includes bibliographical references and index.
• Nota di contenuto: Editors’ Introduction -- Editors’ Introduction -- Invited Papers -- Invention and Artificial Intelligence -- The Arrowsmith Project: 2005 Status Report -- The Robot Scientist Project -- Algorithms and Software for Collaborative Discovery from Autonomous, Semantically Heterogeneous, Distributed Information Sources -- Training Support Vector Machines via SMO-Type Decomposition Methods -- Kernel-Based Learning -- Measuring Statistical Dependence with Hilbert-Schmidt Norms -- An Analysis of the Anti-learning Phenomenon for the Class Symmetric Polyhedron -- Learning Causal Structures Based on Markov Equivalence Class -- Stochastic Complexity for Mixture of Exponential Families in Variational Bayes -- ACME: An Associative Classifier Based on Maximum Entropy Principle -- Constructing Multiclass Learners from Binary Learners: A Simple Black-Box Analysis of the Generalization Errors -- On Computability of Pattern Recognition Problems -- PAC-Learnability of Probabilistic Deterministic Finite State Automata in Terms of Variation Distance -- Learnability of Probabilistic Automata via Oracles -- Learning Attribute-Efficiently with Corrupt Oracles -- Learning DNF by Statistical and Proper Distance Queries Under the Uniform Distribution -- Learning of Elementary Formal Systems with Two Clauses Using Queries -- Gold-Style and Query Learning Under Various Constraints on the Target Class -- Non U-Shaped Vacillatory and Team Learning -- Learning Multiple Languages in Groups -- Inferring Unions of the Pattern Languages by the Most Fitting Covers -- Identification in the Limit of Substitutable Context-Free Languages -- Algorithms for Learning Regular Expressions -- A Class of Prolog Programs with Non-linear Outputs Inferable from Positive Data -- Absolute Versus Probabilistic Classification in a Logical Setting -- Online Allocation with Risk Information -- Defensive Universal Learning with Experts -- On Following the Perturbed Leader in the Bandit Setting -- Mixture of Vector Experts -- On-line Learning with Delayed Label Feedback -- Monotone Conditional Complexity Bounds on Future Prediction Errors -- Non-asymptotic Calibration and Resolution -- Defensive Prediction with Expert Advice -- Defensive Forecasting for Linear Protocols -- Teaching Learners with Restricted Mind Changes.
• Titolo autorizzato: Algorithmic Learning Theory
• ISBN: 3-540-31696-5; 3-540-29242-X
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 996466223003316
• Lo trovi qui: Univ. di Salerno
• Serie: Lecture Notes in Artificial Intelligence ; ; 3734