Encyclopedia of Machine Learning by Claude Sammut, Geoffrey I. Webb

By Claude Sammut, Geoffrey I. Webb

Claude Sammut is a Professor of machine technological know-how and Engineering on the collage of latest South Wales, Australia, and Head of the bogus Intelligence study workforce. he's the UNSW node Director of the ARC Centre of Excellence for self reliant structures and a member of the joint ARC/NH&MRC venture on pondering platforms. he's at the editorial forums of the magazine of laptop studying examine, the computing device studying magazine and New iteration Computing, and was once the chairman of the 2007 overseas convention on laptop Learning.

Geoffrey I. Webb is learn professor within the college of knowledge know-how at Monash collage, Melbourne, Australia. He has released greater than a hundred and fifty medical papers and is the writer of the knowledge mining software program package deal Magnum Opus. His study parts contain ideas for strengthening the Naïve Bayes laptop studying approach, K-optimal trend discovery, and paintings on Occam’s razor. he's editor-in-chief of Springer’s facts Mining and data Discovery magazine, in addition to being at the editorial board of laptop Learning.

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In Proceedings of the th international conference on inductive logic programming (pp. –). Berlin: Springer. Moyle, S. A. (). An investigation into theory completion techniques in inductive logic programming. PhD thesis, Oxford University Computing Laboratory, University of Oxford. Muggleton, S. (). Inverse entailment and Progol. New Generation Computing, , –. , & Bryant, C. (). Theory completion using inverse entailment. In Proceedings of the tenth international workshop on inductive logic programming (ILP-) (pp.

Here the abductive reasoning can be used to suitably connect and integrate the learning of the different predicates. This can help to overcome some of the nonlocality difficulties of multiple predicate learning, such as order-dependence and global consistency of the learned theory. ACL is defined as an extension of Inductive Logic Programming (ILP) where both the background knowledge and the learned theory are abductive theories. The central formal definition of ACL is given as follows where examples are atomic ground facts on the target predicate(s) to be learned.

Proceedings of the sixth international workshop on machine learning. Ithaca, NY. Seung, H. , & Sompolinsky, H. (). Query by committee. In Proceedings of the fifth workshop on computational learning theory (pp. –). San Mateo, CA: Morgan Kaufmann. , & Jaakkola, T. (). Unsupervised active learning in large domains. In Proceeding of the conference on uncertainty in AI. html Active Learning Theory Sanjoy Dasgupta University of California, San Diego, La Jolla, CA, USA Definition The term active learning applies to a wide range of situations in which a learner is able to exert some control over its source of data.

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