A Convex Optimization Framework for Active Learning

In many image/video/web classification problems, we have access to a large number of unlabeled samples. However, it is typically expensive and time consuming to obtain labels for the samples. Active learning is the problem of progressively selecting and annotating the most informative unlabeled samp...

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Veröffentlicht in:	2013 IEEE International Conference on Computer Vision S. 209 - 216
Hauptverfasser:	Elhamifar, Ehsan, Sapiro, Guillermo, Yang, Allen, Sasrty, S. Shankar
Format:	Tagungsbericht Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.12.2013
Schlagworte:	Algorithms Classification Classifiers Computational geometry Computer vision Convex functions Convexity Encoding Labeling Learning Optimization Retraining Support vector machines Training Uncertainty
ISSN:	1550-5499
Online-Zugang:	Volltext
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