Publikation: Showing the Equivalence of Two Training Algorithms, I
Lade...
Dateien
Zu diesem Dokument gibt es keine Dateien.
Datum
1998
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Beitrag zu einem Konferenzband
Publikationsstatus
Published
Erschienen in
1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227). IEEE, 1998, pp. 447-456. ISBN 0-7803-4859-1. Available under: doi: 10.1109/IJCNN.1998.682308
Zusammenfassung
Graph transformations offer a powerful way to formally specify neural networks and their corresponding training algorithms. This formalism can be used to prove properties of these algorithms. In this paper graph transformations are used to show the equivalence of two training algorithms for recurrent neural networks; backpropagation through time, and a variant of real-time backpropagation. In addition to this proof a whole class of related training algorithms emerges from the used formalism.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Konferenz
ICNN '98 - International Conference on Neural Networks, Anchorage, AK, USA
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690
KOCH, Manuel, Ingrid FISCHER, Michael R. BERTHOLD, 1998. Showing the Equivalence of Two Training Algorithms, I. ICNN '98 - International Conference on Neural Networks. Anchorage, AK, USA. In: 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227). IEEE, 1998, pp. 447-456. ISBN 0-7803-4859-1. Available under: doi: 10.1109/IJCNN.1998.682308BibTex
@inproceedings{Koch1998Showi-24290, year={1998}, doi={10.1109/IJCNN.1998.682308}, title={Showing the Equivalence of Two Training Algorithms, I}, isbn={0-7803-4859-1}, publisher={IEEE}, booktitle={1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227)}, pages={447--456}, author={Koch, Manuel and Fischer, Ingrid 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/123456789/24290"> <dc:rights>terms-of-use</dc:rights> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-22T08:22:22Z</dc:date> <dcterms:issued>1998</dcterms:issued> <dc:creator>Fischer, Ingrid</dc:creator> <dc:creator>Berthold, Michael R.</dc:creator> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24290"/> <dcterms:title>Showing the Equivalence of Two Training Algorithms, I</dcterms:title> <dc:contributor>Koch, Manuel</dc:contributor> <dc:contributor>Fischer, Ingrid</dc:contributor> <dc:creator>Koch, Manuel</dc:creator> <dcterms:abstract xml:lang="eng">Graph transformations offer a powerful way to formally specify neural networks and their corresponding training algorithms. This formalism can be used to prove properties of these algorithms. In this paper graph transformations are used to show the equivalence of two training algorithms for recurrent neural networks; backpropagation through time, and a variant of real-time backpropagation. In addition to this proof a whole class of related training algorithms emerges from the used formalism.</dcterms:abstract> <foaf:homepage rdf:resource="http://localhost:8080/"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:language>eng</dc:language> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dc:contributor>Berthold, Michael R.</dc:contributor> <dcterms:bibliographicCitation>The 1998 IEEE International Joint Conference on Neural Networks Proceedings : IEEE World Congress on Computational Intelligence : May 4-May 9, 1998, Anchorage, Alaska, USA / [general chair: Patrick K. Simpson]. Piscataway : IEEE Service Center, 1998. - S. 447-456. - ISBN 0-7803-4859-1</dcterms:bibliographicCitation> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-22T08:22:22Z</dcterms:available> </rdf:Description> </rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein