Incremental Active Learning with Bias Reduction

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IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1

Como, Italy

July 24-July 27

ISBN: 0-7695-0619-4

	ASCII Text	x
	Masashi Sugiyama, Hidemitsu Ogawa, "Incremental Active Learning with Bias Reduction," Neural Networks, IEEE - INNS - ENNS International Joint Conference on, vol. 1, pp. 1015, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1, 2000.

	BibTex	x
	@article{ 10.1109/IJCNN.2000.857807, author = {Masashi Sugiyama and Hidemitsu Ogawa}, title = {Incremental Active Learning with Bias Reduction}, journal ={Neural Networks, IEEE - INNS - ENNS International Joint Conference on}, volume = {1}, year = {2000}, issn = {1098-7576}, pages = {1015}, doi = {http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857807}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Neural Networks, IEEE - INNS - ENNS International Joint Conference on TI - Incremental Active Learning with Bias Reduction SN - 1098-7576 SP EP A1 - Masashi Sugiyama, A1 - Hidemitsu Ogawa, PY - 2000 VL - 1 JA - Neural Networks, IEEE - INNS - ENNS International Joint Conference on ER -

Masashi Sugiyama, Tokyo Institute of Technology

Hidemitsu Ogawa, Tokyo Institute of Technology

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/IJCNN.2000.857807

The problem of designing input signals for optimal generalization in supervised learning is called active learning. In many active learning methods devised so far, the bias of the learning results is assumed zero. In this paper, we remove this assumption and propose a new active learning method with the bias reduction. The effectiveness of the proposed methods demonstrated through computer simulations.

Citation:

Masashi Sugiyama, Hidemitsu Ogawa, "Incremental Active Learning with Bias Reduction," ijcnn, vol. 1, pp.1015, IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 1, 2000

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