Abstract

Active learning techniques have gained popularity to reduce human effort in labeling data instances for inducing a classifier. When faced with large amounts of unlabeled data, such algorithms automatically identify the exemplar and representative instances to be selected for manual annotation. More recently, there have been attempts towards a batch mode form of active learning, where a batch of data points is simultaneously selected from an unlabeled set. Real-world applications require adaptive approaches for batch selection in active learning. However, existing work in this field has primarily been heuristic and static. In this work, we propose a novel optimization-based framework for dynamic batch mode active learning, where the batch size as well as the selection criteria are combined in a single formulation. The solution procedure has the same computational complexity as existing state-of-the-art static batch mode active learning techniques. Our results on four challenging biometric datasets portray the efficacy of the proposed framework and also certify the potential of this approach in being used for real world biometric recognition applications.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Pages2649-2656
Number of pages8
DOIs
StatePublished - 2011
Event2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, CO, United States
Duration: Jun 20 2011Jun 25 2011

Other

Other2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
CountryUnited States
CityColorado Springs, CO
Period6/20/116/25/11

Fingerprint

Biometrics
Labeling
Computational complexity
Classifiers
Problem-Based Learning

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

Cite this

Chakraborty, S., Balasubramanian, V., & Panchanathan, S. (2011). Dynamic batch mode active learning. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 (pp. 2649-2656). [5995715] https://doi.org/10.1109/CVPR.2011.5995715

Dynamic batch mode active learning. / Chakraborty, Shayok; Balasubramanian, Vineeth; Panchanathan, Sethuraman.

2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. p. 2649-2656 5995715.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chakraborty, S, Balasubramanian, V & Panchanathan, S 2011, Dynamic batch mode active learning. in 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011., 5995715, pp. 2649-2656, 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011, Colorado Springs, CO, United States, 6/20/11. https://doi.org/10.1109/CVPR.2011.5995715
Chakraborty S, Balasubramanian V, Panchanathan S. Dynamic batch mode active learning. In 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. p. 2649-2656. 5995715 https://doi.org/10.1109/CVPR.2011.5995715
Chakraborty, Shayok ; Balasubramanian, Vineeth ; Panchanathan, Sethuraman. / Dynamic batch mode active learning. 2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011. 2011. pp. 2649-2656
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