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Kernels on Prolog Proof Trees:Statistical Learning in the ILP Setting Passerini, Andrea Frasconi, Paolo De Raedt, Luc Proof Trees Logic Kernels Learning from Traces 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Andrea Passerini and Paolo Frasconi and Luc De Raedt 2006 Is Part Of Dagstuhl Seminar Proceedings, Volume 5051, Probabilistic, Logical and Relational Learning - Towards a Synthesis (2006) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.05051.8 urn:nbn:de:0030-drops-4171 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.05051.8 eng https://creativecommons.org/licenses/by/4.0/legalcode