Algorithmic Learning Theory 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006. Proceedings /

Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Balcázar, José L. (Επιμελητής έκδοσης), Long, Philip M. (Επιμελητής έκδοσης), Stephan, Frank (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2006.
Σειρά:Lecture Notes in Computer Science, 4264
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Algorithmic Learning Theory  |h [electronic resource] :  |b 17th International Conference, ALT 2006, Barcelona, Spain, October 7-10, 2006. Proceedings /  |c edited by José L. Balcázar, Philip M. Long, Frank Stephan. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2006. 
300 |a XIII, 393 p.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
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490 1 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |v 4264 
505 0 |a 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. 
650 0 |a Computer science. 
650 0 |a Computers. 
650 0 |a Algorithms. 
650 0 |a Mathematical logic. 
650 0 |a Artificial intelligence. 
650 0 |a Text processing (Computer science). 
650 1 4 |a Computer Science. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Computation by Abstract Devices. 
650 2 4 |a Algorithm Analysis and Problem Complexity. 
650 2 4 |a Mathematical Logic and Formal Languages. 
650 2 4 |a Document Preparation and Text Processing. 
700 1 |a Balcázar, José L.  |e editor. 
700 1 |a Long, Philip M.  |e editor. 
700 1 |a Stephan, Frank.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783540466499 
830 0 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |v 4264 
856 4 0 |u http://dx.doi.org/10.1007/11894841  |z Full Text via HEAL-Link 
912 |a ZDB-2-SCS 
912 |a ZDB-2-LNC 
950 |a Computer Science (Springer-11645)