ISBN: 9783540466499 - algorithmic learning theory: 17th international conference, alt 2006, barcelona, spain, october 7-10, 2006, proceedings: 4264 (lecture notes in computer science, 4264) (14 resultados)

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New. In English.

Condición: As New. Unread book in perfect condition.

Condición: New. pp. 412.

Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 fromStationary Processes.- Learning-Related Complexity of Linear Ranking Functions.…

PF. Condición: New. This item is printed on demand. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006.The 24 revised full papers presented together with the abstracts of five invited papers were carefully reviewed and selected from 53 submissions. The papers are dedicated to the theoretical foundations of machine learning. 412 pp. Englisch.…

Condición: New. Print on Demand pp. 412 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book constitutes the refereed proceedings of the 17th International Conference on Algorithmic Learning Theory, ALT 2006, held in Barcelona, Spain in October 2006, colocated with the 9th International Conference on Discovery Science, DS 2006.T.…

Condición: New. PRINT ON DEMAND pp. 412.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 fromStationary Processes.- Learning-Related Complexity of Linear Ranking Functions.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 412 pp. Englisch. …

Taschenbuch. Condición: Neu. Algorithmic Learning Theory | 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006, Proceedings | José L. Balcázar (u. a.) | Taschenbuch | xiii | Englisch | 2006 | Springer | EAN 9783540466499 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.…