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Titolo: |
Algorithmic Learning Theory [[electronic resource] ] : 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings / / edited by José L. Balcázar, Philip M. Long, Frank Stephan
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Pubblicazione: | Berlin, Heidelberg : , : Springer Berlin Heidelberg : , : Imprint : Springer, , 2006 |
Edizione: | 1st ed. 2006. |
Descrizione fisica: | 1 online resource (XIII, 393 p.) |
Disciplina: | 006.31 |
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.): | BalcázarJosé L |
LongPhilip M | |
StephanFrank | |
Note generali: | Bibliographic Level Mode of Issuance: Monograph |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Editors’ Introduction -- Editors’ Introduction -- Invited Contributions -- Solving Semi-infinite Linear Programs Using Boosting-Like Methods -- e-Science and the Semantic Web: A Symbiotic Relationship -- Spectral Norm in Learning Theory: Some Selected Topics -- Data-Driven Discovery Using Probabilistic Hidden Variable Models -- Reinforcement Learning and Apprenticeship Learning for Robotic Control -- Regular Contributions -- Learning Unions of ?(1)-Dimensional Rectangles -- On Exact Learning Halfspaces with Random Consistent Hypothesis Oracle -- Active Learning in the Non-realizable Case -- How Many Query Superpositions Are Needed to Learn? -- Teaching Memoryless Randomized Learners Without Feedback -- The Complexity of Learning SUBSEQ (A) -- Mind Change Complexity of Inferring Unbounded Unions of Pattern Languages from Positive Data -- Learning and Extending Sublanguages -- Iterative Learning from Positive Data and Negative Counterexamples -- Towards a Better Understanding of Incremental Learning -- On Exact Learning from Random Walk -- Risk-Sensitive Online Learning -- Leading Strategies in Competitive On-Line Prediction -- Hannan Consistency in On-Line Learning in Case of Unbounded Losses Under Partial Monitoring -- General Discounting Versus Average Reward -- The Missing Consistency Theorem for Bayesian Learning: Stochastic Model Selection -- Is There an Elegant Universal Theory of Prediction? -- Learning Linearly Separable Languages -- Smooth Boosting Using an Information-Based Criterion -- Large-Margin Thresholded Ensembles for Ordinal Regression: Theory and Practice -- Asymptotic Learnability of Reinforcement Problems with Arbitrary Dependence -- Probabilistic Generalization of Simple Grammars and Its Application to Reinforcement Learning -- Unsupervised Slow Subspace-Learning from Stationary Processes -- Learning-Related Complexity of Linear Ranking Functions. |
Titolo autorizzato: | Algorithmic Learning Theory ![]() |
ISBN: | 3-540-46650-9 |
Formato: | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996466021703316 |
Lo trovi qui: | Univ. di Salerno |
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