@inproceedings{3f240841f9134035974e7dacf5e4d509,
title = "Augmented embedding of dissimilarity data into (pseudo-)Euclidean spaces",
abstract = "Pairwiseproximitiesdescribethepropertiesofobjectsintermsoftheirsimilarities.Byusingdi¿erentdistance-basedfunctionsonemayencodedi¿erentcharacteristicsofagivenproblem.However,tousetheframeworkofstatisticalpatternrecognitionsomevectorrepresentationshouldbeconstructed.Oneofthesimplestwaystodothatistode¿neanisometricembeddingtosomevectorspace.Inthiswork,wewillfocusonalinearembeddingintoa(pseudo-)Euclideanspace. Thisisusuallywellde¿nedfortrainingdata.Someinadequacy,however,appearswhenprojectingnewortestobjectsduetotheresultingprojectionerrors.Inthispaperweproposeanaugmentedembeddingalgorithmthatenlargesthedimensionalityofthespacesuchthattheresultingprojectionerrorvanishes.Ourpreliminaryresultsshowthatitmayleadtoabetterclassi¿cationaccuracy,especiallyfordatawithhighintrinsicdimensionality.",
keywords = "conference contrib. refereed, CWTS 0.75 <= JFIS < 2.00",
author = "A Harol and EM Pekalska and S Verzakov and RPW Duin",
year = "2006",
language = "Undefined/Unknown",
publisher = "Springer",
pages = "613--621",
editor = "DY Yeung and JT Kwok and A Fred and F Roli and {de Ridder}, D",
booktitle = "Structural, syntactic and statistical pattern recognition",
note = "null ; Conference date: 17-08-2006 Through 19-08-2006",
}