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URN: urn:nbn:de:0030-drops-4171
URL: http://drops.dagstuhl.de/opus/volltexte/2006/417/

Passerini, Andrea ; Frasconi, Paolo ; De Raedt, Luc

Kernels on Prolog Proof Trees:Statistical Learning in the ILP Setting

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Abstract

An example-trace is a sequence of steps taken by a program on a given example input. Different approaches exist in order to exploit example-traces for learning, all explicitly inferring a target program from positive and negative traces. We generalize such idea by developing similarity measures betweeen traces in order to learn to discriminate between positive and negative ones. This allows to combine the expressiveness of inductive logic programming in representing knowledge to the statistical properties of kernel machines. Logic programs will be used to generate proofs of given visitor programs which exploit the available background knowledge, while kernel machines will be employed to learn from such proofs.

BibTeX - Entry

@InProceedings{passerini_et_al:DSP:2006:417,
  author =	{Andrea Passerini and Paolo Frasconi and Luc De Raedt},
  title =	{Kernels on Prolog Proof Trees:Statistical Learning in the ILP Setting},
  booktitle =	{Probabilistic, Logical and Relational Learning - Towards a Synthesis},
  year =	{2006},
  editor =	{Luc De Raedt and Thomas Dietterich and Lise Getoor  and Stephen H. Muggleton},
  number =	{05051},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2006/417},
  annote =	{Keywords: Proof Trees, Logic Kernels, Learning from Traces}
}

Keywords: Proof Trees, Logic Kernels, Learning from Traces
Seminar: 05051 - Probabilistic, Logical and Relational Learning - Towards a Synthesis
Issue date: 2006
Date of publication: 19.01.2006


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