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» A Model of Inductive Bias Learning
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ICANN
2003
Springer
14 years 20 days ago
Learning Rule Representations from Boolean Data
We discuss a Probably Approximate Correct (PAC) learning paradigm for Boolean formulas, which we call PAC meditation, where the class of formulas to be learnt is not known in advan...
Bruno Apolloni, Andrea Brega, Dario Malchiodi, Gio...
AICOM
2006
105views more  AICOM 2006»
13 years 7 months ago
Evolutionary concept learning in First Order Logic: An overview
This paper presents an overview of recent systems for Inductive Logic Programming (ILP). After a short description of the two popular ILP systems FOIL and Progol, we focus on meth...
Federico Divina
ICML
2004
IEEE
14 years 8 months ago
Learning and evaluating classifiers under sample selection bias
Classifier learning methods commonly assume that the training data consist of randomly drawn examples from the same distribution as the test examples about which the learned model...
Bianca Zadrozny
ALT
2006
Springer
14 years 4 months ago
The Complexity of Learning SUBSEQ (A)
Higman showed that if A is any language then SUBSEQ(A) is regular, where SUBSEQ(A) is the language of all subsequences of strings in A. We consider the following inductive inferenc...
Stephen A. Fenner, William I. Gasarch
ICML
2003
IEEE
14 years 8 months ago
Robust Induction of Process Models from Time-Series Data
Pat Langley, Dileep George, Stephen D. Bay, Kazumi...