Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors

Lade...
Vorschaubild
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
2018
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
DUIVESTEIJN, Wouter, ed., Arno SIEBES, ed., Antti UKKONEN, ed.. Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings. Cham: Springer, 2018, pp. 264-277. Lecture Notes in Computer Science. 11191. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-01767-5. Available under: doi: 10.1007/978-3-030-01768-2_22
Zusammenfassung

Widening is a method where parallel resources are used to find better solutions from algorithms instead of merely trying to find the same solutions more quickly. To date, every example of Widening has used some from of communiucation between the parallel workers to maintain their distances from one another in the model space. For the first time, we present a communication-free, widened extension to a standard machine learning algorithm. By using Locality Sensitive Hashing on the Bayesian networks' Fiedler vectors, we demonstrate the ability to learn classifiers superior to those standard implementations and to those generated with a greedy heuristic alone

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
17th International Symposium, IDA 2018, 24. Okt. 2018 - 26. Okt. 2018, ’s-Hertogenbosch, The Netherlands
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690SAMPSON, Oliver R., Christian BORGELT, Michael R. BERTHOLD, 2018. Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors. 17th International Symposium, IDA 2018. ’s-Hertogenbosch, The Netherlands, 24. Okt. 2018 - 26. Okt. 2018. In: DUIVESTEIJN, Wouter, ed., Arno SIEBES, ed., Antti UKKONEN, ed.. Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings. Cham: Springer, 2018, pp. 264-277. Lecture Notes in Computer Science. 11191. ISSN 0302-9743. eISSN 1611-3349. ISBN 978-3-030-01767-5. Available under: doi: 10.1007/978-3-030-01768-2_22
BibTex
@inproceedings{Sampson2018-10-05Commu-44696,
  year={2018},
  doi={10.1007/978-3-030-01768-2_22},
  title={Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors},
  number={11191},
  isbn={978-3-030-01767-5},
  issn={0302-9743},
  publisher={Springer},
  address={Cham},
  series={Lecture Notes in Computer Science},
  booktitle={Advances in Intelligent Data Analysis XVII : 17th International Symposium, IDA 2018, ’s-Hertogenbosch, The Netherlands, October 24-26, 2018, proceedings},
  pages={264--277},
  editor={Duivesteijn, Wouter and Siebes, Arno and Ukkonen, Antti},
  author={Sampson, Oliver R. and Borgelt, Christian and Berthold, Michael R.}
}
RDF
<rdf:RDF
    xmlns:dcterms="http://purl.org/dc/terms/"
    xmlns:dc="http://purl.org/dc/elements/1.1/"
    xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
    xmlns:bibo="http://purl.org/ontology/bibo/"
    xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#"
    xmlns:foaf="http://xmlns.com/foaf/0.1/"
    xmlns:void="http://rdfs.org/ns/void#"
    xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > 
  <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/44696">
    <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Borgelt, Christian</dc:contributor>
    <bibo:uri rdf:resource="https://kops.uni-konstanz.de/handle/123456789/44696"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dc:rights>terms-of-use</dc:rights>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/44696/1/Sampson_2-bn89p9g927ii7.pdf"/>
    <dcterms:title>Communication-Free Widened Learning of Bayesian Network Classifiers Using Hashed Fiedler Vectors</dcterms:title>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-23T13:44:40Z</dc:date>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2019-01-23T13:44:40Z</dcterms:available>
    <dcterms:issued>2018-10-05</dcterms:issued>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dc:language>eng</dc:language>
    <dc:creator>Borgelt, Christian</dc:creator>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dcterms:abstract xml:lang="eng">Widening is a method where parallel resources are used to find better solutions from algorithms instead of merely trying to find the same solutions more quickly. To date, every example of Widening has used some from of communiucation between the parallel workers to maintain their distances from one another in the model space. For the first time, we present a communication-free, widened extension to a standard machine learning algorithm. By using Locality Sensitive Hashing on the Bayesian networks' Fiedler vectors, we demonstrate the ability to learn classifiers superior to those standard implementations and to those generated with a greedy heuristic alone</dcterms:abstract>
    <dc:contributor>Sampson, Oliver R.</dc:contributor>
    <dc:creator>Sampson, Oliver R.</dc:creator>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/44696/1/Sampson_2-bn89p9g927ii7.pdf"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Ja
Begutachtet
Diese Publikation teilen