Show simple item record

dc.contributor.authorMatias, Alan L. S.
dc.contributor.authorMattos, César L. C.
dc.contributor.authorKärkkäinen, Tommi
dc.contributor.authorGomes, João P. P.
dc.contributor.authorRocha Neto, Ajalmar R. da
dc.contributor.editorRojas, Ignacio
dc.contributor.editorJoya, Gonzalo
dc.contributor.editorCatala, Andreu
dc.date.accessioned2019-10-17T09:17:44Z
dc.date.available2019-10-17T09:17:44Z
dc.date.issued2019
dc.identifier.citationMatias, Alan L. S.; Mattos, César L. C.; Kärkkäinen, Tommi; Gomes, João P. P.; Rocha Neto, Ajalmar R. da (2019). OnMLM : An Online Formulation for the Minimal Learning Machine. In Rojas, Ignacio; Joya, Gonzalo; Catala, Andreu (Eds.) IWANN 2019 : Advances in Computational Intelligence : 15th International Work-Conference on Artificial Neural Networks, Proceedings, Part I, Lecture Notes in Computer Science, 11506. Cham: Springer, 557-568. DOI: 10.1007/978-3-030-20521-8_46
dc.identifier.otherCONVID_32145299
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/65933
dc.description.abstractMinimal Learning Machine (MLM) is a nonlinear learning algorithm designed to work on both classification and regression tasks. In its original formulation, MLM builds a linear mapping between distance matrices in the input and output spaces using the Ordinary Least Squares (OLS) algorithm. Although the OLS algorithm is a very efficient choice, when it comes to applications in big data and streams of data, online learning is more scalable and thus applicable. In that regard, our objective of this work is to propose an online version of the MLM. The Online Minimal Learning Machine (OnMLM), a new MLM-based formulation capable of online and incremental learning. The achievements of OnMLM in our experiments, in both classification and regression scenarios, indicate its feasibility for applications that require an online learning framework.en
dc.format.extent940
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.publisherSpringer
dc.relation.ispartofIWANN 2019 : Advances in Computational Intelligence : 15th International Work-Conference on Artificial Neural Networks, Proceedings, Part I
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rightsIn Copyright
dc.subject.otheronline learning
dc.subject.otherincremental learning
dc.subject.otherstochastic optimization
dc.subject.otherMinimal Learning Machine
dc.titleOnMLM : An Online Formulation for the Minimal Learning Machine
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201910174506
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.relation.isbn978-3-030-20520-1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange557-568
dc.relation.issn0302-9743
dc.type.versionacceptedVersion
dc.rights.copyright© Springer International Publishing AG 2019
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Work-Conference on Artificial Neural Networks
dc.relation.grantnumber311877
dc.relation.grantnumber315550
dc.subject.ysostokastiset prosessit
dc.subject.ysokoneoppiminen
dc.subject.ysobig data
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p11400
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
jyx.subject.urihttp://www.yso.fi/onto/yso/p27202
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-030-20521-8_46
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
dc.relation.funderAcademy of Finlanden
jyx.fundingprogramMuut, SAfi
jyx.fundingprogramAkatemiaohjelma, SAfi
jyx.fundingprogramOthers, AoFen
jyx.fundingprogramAcademy Programme, AoFen
jyx.fundinginformationThe work was supported by the Academy of Finland from grants 311877 and 315550.


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record

In Copyright
Except where otherwise noted, this item's license is described as In Copyright