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Titlebook: Inductive Logic Programming; 10th International C James Cussens,Alan Frisch Conference proceedings 2000 Springer-Verlag Berlin Heidelberg 2

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發(fā)表于 2025-3-28 15:12:32 | 只看該作者
Theory Completion Using Inverse Entailmentboth the examples and hypotheses define the same predicate. However, in both scientific discovery and language learning potential applications exist in which OPL does not hold. OPL is ingrained within the theory and performance testing of Machine Learning. A general ILP technique called “Theory Comp
42#
發(fā)表于 2025-3-28 21:57:17 | 只看該作者
Solving Selection Problems Using Preference Relation Based on Bayesian Learningf selection problems and give a method combining inductive logic programming (ILP) and Bayesian learning. It induces a binary relation comparing likelihood of objects being selected. Our methods estimate probability of each choice by evaluating variance of an induced relation from an ideal binary re
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發(fā)表于 2025-3-29 01:31:09 | 只看該作者
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發(fā)表于 2025-3-29 03:09:34 | 只看該作者
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發(fā)表于 2025-3-29 11:19:17 | 只看該作者
Towards Learning in CARIN-,Logics. Our goal is to study the feasability of learning in such a hybrid description - horn clause language, namely CARIN-. [.], in the presence of hybrid background knowledge, including a Horn clause and a terminological component. After setting our learning framework, we present algorithms for te
46#
發(fā)表于 2025-3-29 14:36:06 | 只看該作者
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發(fā)表于 2025-3-29 16:15:43 | 只看該作者
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發(fā)表于 2025-3-29 23:02:16 | 只看該作者
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發(fā)表于 2025-3-30 00:21:33 | 只看該作者
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發(fā)表于 2025-3-30 05:27:52 | 只看該作者
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