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Yang, Yazhou, Loog, Marco (2018) A variance maximization criterion for active learning. Pattern Recognition, 78. 358-370 doi:10.1016/j.patcog.2018.01.017

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Reference TypeJournal (article/letter/editorial)
TitleA variance maximization criterion for active learning
JournalPattern Recognition
AuthorsYang, YazhouAuthor
Loog, MarcoAuthor
Year2018 (June)Volume78
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2018.01.017Search in ResearchGate
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Mindat Ref. ID9367347Long-form Identifiermindat:1:5:9367347:7
GUID0
Full ReferenceYang, Yazhou, Loog, Marco (2018) A variance maximization criterion for active learning. Pattern Recognition, 78. 358-370 doi:10.1016/j.patcog.2018.01.017
Plain TextYang, Yazhou, Loog, Marco (2018) A variance maximization criterion for active learning. Pattern Recognition, 78. 358-370 doi:10.1016/j.patcog.2018.01.017
In(2018) Pattern Recognition Vol. 78. Elsevier BV

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Yang, Yazhou, Loog, Marco (2018) A benchmark and comparison of active learning for logistic regression. Pattern Recognition, 83. 401-415 doi:10.1016/j.patcog.2018.06.004
Yang, Yazhou, Loog, Marco (2022) To Actively Initialize Active Learning. Pattern Recognition, 131. 108836 doi:10.1016/j.patcog.2022.108836
Yang, Yazhou, Loog, Marco (2019) Single shot active learning using pseudo annotators. Pattern Recognition, 89. 22-31 doi:10.1016/j.patcog.2018.12.027
Loog, Marco (2007) On an alternative formulation of the Fisher criterion that overcomes the small sample problem. Pattern Recognition, 40 (6). 1753-1755 doi:10.1016/j.patcog.2006.11.002
Cheplygina, Veronika, Tax, David M.J., Loog, Marco (2015) Multiple instance learning with bag dissimilarities. Pattern Recognition, 48 (1). 264-275 doi:10.1016/j.patcog.2014.07.022
Li, Yan, Tax, David M.J., Duin, Robert P.W., Loog, Marco (2013) Multiple-instance learning as a classifier combining problem. Pattern Recognition, 46 (3). 865-874 doi:10.1016/j.patcog.2012.08.018
Wu, Jianxin, Bai, Xiang, Loog, Marco, Roli, Fabio, Zhou, Zhi-Hua (2017) Editorial of the Special Issue on Multi-instance Learning in Pattern Recognition and Vision. Pattern Recognition, 71. 444-445 doi:10.1016/j.patcog.2017.05.026
Wang, Juan, Yang, Yongyi (2018) A context-sensitive deep learning approach for microcalcification detection in mammograms. Pattern Recognition, 78. 12-22 doi:10.1016/j.patcog.2018.01.009
Qin, A.K., Suganthan, P.N., Loog, M. (2005) Uncorrelated heteroscedastic LDA based on the weighted pairwise Chernoff criterion. Pattern Recognition, 38 (4). 613-616 doi:10.1016/j.patcog.2004.09.007
Krijthe, Jesse H., Loog, Marco (2017) Robust semi-supervised least squares classification by implicit constraints. Pattern Recognition, 63. 115-126 doi:10.1016/j.patcog.2016.09.009
Alpaydın, Ethem, Cheplygina, Veronika, Loog, Marco, Tax, David M.J. (2015) Single- vs. multiple-instance classification. Pattern Recognition, 48 (9). 2831-2838 doi:10.1016/j.patcog.2015.04.006
 
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