Algorithmic Learning Theory 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012. Proceedings /

This book constitutes the refereed proceedings of the 23rd International Conference on Algorithmic Learning Theory, ALT 2012, held in Lyon, France, in October 2012. The conference was co-located and held in parallel with the 15th International Conference on Discovery Science, DS 2012. The 23 full pa...

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Λεπτομέρειες βιβλιογραφικής εγγραφής
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Άλλοι συγγραφείς: Bshouty, Nader H. (Επιμελητής έκδοσης), Stoltz, Gilles (Επιμελητής έκδοσης), Vayatis, Nicolas (Επιμελητής έκδοσης), Zeugmann, Thomas (Επιμελητής έκδοσης)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012.
Σειρά:Lecture Notes in Computer Science, 7568
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Algorithmic Learning Theory  |h [electronic resource] :  |b 23rd International Conference, ALT 2012, Lyon, France, October 29-31, 2012. Proceedings /  |c edited by Nader H. Bshouty, Gilles Stoltz, Nicolas Vayatis, Thomas Zeugmann. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg :  |b Imprint: Springer,  |c 2012. 
300 |a XII, 381 p. 23 illus.  |b online resource. 
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490 1 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |v 7568 
505 0 |a inductive inference -- teaching and PAC learning -- statistical learning theory and classification -- relations between models and data -- bandit problems, online prediction of individual sequences.- other models of online learning. 
520 |a This book constitutes the refereed proceedings of the 23rd International Conference on Algorithmic Learning Theory, ALT 2012, held in Lyon, France, in October 2012. The conference was co-located and held in parallel with the 15th International Conference on Discovery Science, DS 2012. The 23 full papers and 5 invited talks presented were carefully reviewed and selected from 47 submissions. The papers are organized in topical sections on inductive inference, teaching and PAC learning, statistical learning theory and classification, relations between models and data, bandit problems, online prediction of individual sequences, and other models of online learning. 
650 0 |a Computer science. 
650 0 |a Computers. 
650 0 |a Algorithms. 
650 0 |a Computer logic. 
650 0 |a Mathematical logic. 
650 0 |a Artificial intelligence. 
650 0 |a Pattern recognition. 
650 1 4 |a Computer Science. 
650 2 4 |a Artificial Intelligence (incl. Robotics). 
650 2 4 |a Mathematical Logic and Formal Languages. 
650 2 4 |a Algorithm Analysis and Problem Complexity. 
650 2 4 |a Computation by Abstract Devices. 
650 2 4 |a Logics and Meanings of Programs. 
650 2 4 |a Pattern Recognition. 
700 1 |a Bshouty, Nader H.  |e editor. 
700 1 |a Stoltz, Gilles.  |e editor. 
700 1 |a Vayatis, Nicolas.  |e editor. 
700 1 |a Zeugmann, Thomas.  |e editor. 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer eBooks 
776 0 8 |i Printed edition:  |z 9783642341052 
830 0 |a Lecture Notes in Computer Science,  |x 0302-9743 ;  |v 7568 
856 4 0 |u http://dx.doi.org/10.1007/978-3-642-34106-9  |z Full Text via HEAL-Link 
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950 |a Computer Science (Springer-11645)