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Algorithmic learning theory

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This volume includes the papers from the 21st International Conference on Algorithmic Learning Theory (ALT 2010), held in Canberra, Australia, from October 6–8, 2010. The conference was co-located with the 13th International Conference on Discovery Science (DS 2010) and the Machine Learning Summer School. The technical program featured 26 papers selected from 44 submissions, along with five invited talks presented in joint sessions with both conferences. ALT 2010 focused on the theoretical foundations of machine learning and took place at the Australian National University. It served as a platform for high-quality discussions on various topics, including inductive inference, universal prediction, teaching models, grammatical inference, inductive logic programming, query learning, online learning, and more. The conference also addressed semi-supervised and unsupervised learning, clustering, active learning, statistical learning, and applications of algorithmic learning theory. DS 2010, focusing on intelligent data analysis and knowledge discovery, complemented ALT 2010 by exploring methods for scientific knowledge discovery, continuing the tradition of co-location with Algorithmic Learning Theory.

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Algorithmic learning theory, Marcus Hutter

Język
Rok wydania
2010
Oprawa
(miękka)
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Tytuł
Algorithmic learning theory
Język
angielski
Wydawca
Springer
Rok wydania
2010
Oprawa
miękka
ISBN10
3642161073
ISBN13
9783642161070
Seria
Tagi
Ocena
5 z 5
Opis
This volume includes the papers from the 21st International Conference on Algorithmic Learning Theory (ALT 2010), held in Canberra, Australia, from October 6–8, 2010. The conference was co-located with the 13th International Conference on Discovery Science (DS 2010) and the Machine Learning Summer School. The technical program featured 26 papers selected from 44 submissions, along with five invited talks presented in joint sessions with both conferences. ALT 2010 focused on the theoretical foundations of machine learning and took place at the Australian National University. It served as a platform for high-quality discussions on various topics, including inductive inference, universal prediction, teaching models, grammatical inference, inductive logic programming, query learning, online learning, and more. The conference also addressed semi-supervised and unsupervised learning, clustering, active learning, statistical learning, and applications of algorithmic learning theory. DS 2010, focusing on intelligent data analysis and knowledge discovery, complemented ALT 2010 by exploring methods for scientific knowledge discovery, continuing the tradition of co-location with Algorithmic Learning Theory.