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Active Learning Using a Low-Rank Classifier

Babaee, Mohammadreza and Tsoukalas, Stefanos and Babaee, Maryam and Datcu, Mihai (2015) Active Learning Using a Low-Rank Classifier. In: Electrical Engineering (ICEE), 2015 23rd Iranian Conference on, pp. 561-566. 23rd Iranian Conference on Electrical Engineering (ICEE) 2015, 10-14 May 2015, Tehran, Iran. doi: 10.1109/IranianCEE.2015.7146279. ISBN 978-1-4799-1971-0.

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Official URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7146279


The majority of learning algorithms work based on a training dataset. However, labeling the collected data is costly and time consuming. Active learning has gained high attention due to its ability to label a vast amount of unlabeled collected data. However, the performance of the current state-of-the-art methods declines when the number of training data is increasing. In this paper, we propose and study a variant of Support Vector Machine (SVM), namely low-rank classifier, which is regularized by the trace-norm of learning parameters in active learning scenario. We compare this algorithm with the standard SVM algorithms in depth and analyze its computational complexity and optimization solution. Our experimental results confirm, that the proposed method outperforms the other methods for an increasing amount of training data.

Item URL in elib:https://elib.dlr.de/100387/
Document Type:Conference or Workshop Item (Speech)
Title:Active Learning Using a Low-Rank Classifier
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Babaee, MohammadrezaTechnical University Munich, GermanyUNSPECIFIEDUNSPECIFIED
Tsoukalas, StefanosTechnical University Munich, GermanyUNSPECIFIEDUNSPECIFIED
Babaee, MaryamUniversity of IsfahanUNSPECIFIEDUNSPECIFIED
Journal or Publication Title:Electrical Engineering (ICEE), 2015 23rd Iranian Conference on
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Page Range:pp. 561-566
Keywords:Active learning, Low-rank classifier, Trace-norm regularization, SVM
Event Title:23rd Iranian Conference on Electrical Engineering (ICEE) 2015
Event Location:Tehran, Iran
Event Type:international Conference
Event Dates:10-14 May 2015
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren (old)
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Schwarz, Gottfried
Deposited On:04 Dec 2015 11:45
Last Modified:10 May 2016 23:37

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