Results 281 to 288 of about 9,309 (288)

Bayesian Inductive Logic Programming

Proceedings of the seventh annual conference on Computational learning theory - COLT '94, 1994
Inductive Logic Programming (ILP) involves the construction of first-order definite clause theories from examples and background knowledge. Unlike both traditional Machine Learning and Computational Learning Theory, ILP is based on lock-step development of Theory, Implementations and Applications.
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Inductive Programming

Automated Software Engineering, 2001
Pierre Flener, Derek Partridge
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A Perspective on Inductive Logic Programming

1999
The state-of-the-art in inductive logic programming is surveyed by analyzing the approach taken by this field over the past 8 years. The analysis investigates the roles of 1) logic programming and machine learning, 2) theory, techniques and applications, and 3) various technical problems addressed within inductive logic programming.
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Logic Programming and Co-inductive Definitions

2000
This paper aims to define a complete semantics for a class of non-terminating logic programs. Standard approaches to deal with this problem consist in concentrating on programs where infinite derivations can be seen as computing, in the limit, some ”infinite object”. This is usually done by extending the domain of computation with infinite elements and
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Programming by induction

Information Processing Letters, 1972
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Inductive Programming

2011
Flener, Pierre, Schmid, Ute
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Inductive Logic Programming

2005
Stefan Kramer, Bernhard Pfahringer
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On inductive synthesis of programs

1981
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