Skip navigation
Skip navigation

Kernels for Structured Data

Gaertner, Thomas; Lloyd, John; Flach, Peter

Description

Learning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently have researchers started investigating kernels for structured data. This paper describes how kernel definitions can be simplified by identifying the structure of the data and how kernels can be defined on this structure. We propose a kernel for structured data, prove that it is positive definite, and show how it can be...[Show more]

dc.contributor.authorGaertner, Thomas
dc.contributor.authorLloyd, John
dc.contributor.authorFlach, Peter
dc.coverage.spatialSydney Australia
dc.date.accessioned2015-12-13T23:07:16Z
dc.date.available2015-12-13T23:07:16Z
dc.date.createdJuly 9 2002
dc.identifier.isbn0302-9743
dc.identifier.urihttp://hdl.handle.net/1885/86129
dc.description.abstractLearning from structured data is becoming increasingly important. However, most prior work on kernel methods has focused on learning from attribute-value data. Only recently have researchers started investigating kernels for structured data. This paper describes how kernel definitions can be simplified by identifying the structure of the data and how kernels can be defined on this structure. We propose a kernel for structured data, prove that it is positive definite, and show how it can be adapted in practical applications.
dc.publisherSpringer
dc.relation.ispartofseriesInternational Conference on Inductive Logic Programming (ILP 2002)
dc.sourceInductive Logic Programming: Revised Papers of 12th International Conference, ILP 2002
dc.subjectKeywords: Attribute-value data; Kernel definitions; Kernels; Structured data; Artificial intelligence; Data reduction; Data structures; Logic programming; Learning systems
dc.titleKernels for Structured Data
dc.typeConference paper
local.description.notesImported from ARIES
local.description.refereedYes
dc.date.issued2003
local.identifier.absfor080109 - Pattern Recognition and Data Mining
local.identifier.absfor080203 - Computational Logic and Formal Languages
local.identifier.ariespublicationMigratedxPub14901
local.type.statusPublished Version
local.contributor.affiliationGaertner, Thomas, Fraunhofer Institute
local.contributor.affiliationLloyd, John, College of Engineering and Computer Science, ANU
local.contributor.affiliationFlach, Peter, University of Bristol
local.bibliographicCitation.startpage66
local.bibliographicCitation.lastpage83
dc.date.updated2016-02-24T09:47:17Z
local.identifier.scopusID2-s2.0-7044227547
CollectionsANU Research Publications

Download

There are no files associated with this item.


Items in Open Research are protected by copyright, with all rights reserved, unless otherwise indicated.

Updated:  22 January 2019/ Responsible Officer:  University Librarian/ Page Contact:  Library Systems & Web Coordinator