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Chang, Chin-Chun (2012) A boosting approach for supervised Mahalanobis distance metric learning. Pattern Recognition, 45 (2). 844-862 doi:10.1016/j.patcog.2011.07.026

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Reference TypeJournal (article/letter/editorial)
TitleA boosting approach for supervised Mahalanobis distance metric learning
JournalPattern Recognition
AuthorsChang, Chin-ChunAuthor
Year2012 (February)Volume45
Issue2
PublisherElsevier BV
DOIdoi:10.1016/j.patcog.2011.07.026Search in ResearchGate
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Mindat Ref. ID9365084Long-form Identifiermindat:1:5:9365084:7
GUID0
Full ReferenceChang, Chin-Chun (2012) A boosting approach for supervised Mahalanobis distance metric learning. Pattern Recognition, 45 (2). 844-862 doi:10.1016/j.patcog.2011.07.026
Plain TextChang, Chin-Chun (2012) A boosting approach for supervised Mahalanobis distance metric learning. Pattern Recognition, 45 (2). 844-862 doi:10.1016/j.patcog.2011.07.026
In(2012, February) Pattern Recognition Vol. 45 (2) Elsevier BV

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Chang, Chin-Chun (2010) Generalized iterative RELIEF for supervised distance metric learning. Pattern Recognition, 43 (8). 2971-2981 doi:10.1016/j.patcog.2010.02.024
Xiang, Shiming, Nie, Feiping, Zhang, Changshui (2008) Learning a Mahalanobis distance metric for data clustering and classification. Pattern Recognition, 41 (12). 3600-3612 doi:10.1016/j.patcog.2008.05.018
Chang, Chin-Chun, Chen, Hsin-Yi (2012) Semi-supervised clustering with discriminative random fields. Pattern Recognition, 45 (12). 4402-4413 doi:10.1016/j.patcog.2012.05.021
Nguyen, Bac, De Baets, Bernard (2018) An approach to supervised distance metric learning based on difference of convex functions programming. Pattern Recognition, 81. 562-574 doi:10.1016/j.patcog.2018.04.024
Raducanu, B., Dornaika, F. (2012) A supervised non-linear dimensionality reduction approach for manifold learning. Pattern Recognition, 45 (6). 2432-2444 doi:10.1016/j.patcog.2011.12.006
Nguyen, Bac, Morell, Carlos, De Baets, Bernard (2017) Supervised distance metric learning through maximization of the Jeffrey divergence. Pattern Recognition, 64. 215-225 doi:10.1016/j.patcog.2016.11.010
Chang, Xinyuan, Ma, Zhiheng, Wei, Xing, Hong, Xiaopeng, Gong, Yihong (2020) Transductive semi-supervised metric learning for person re-identification. Pattern Recognition, 108. 107569pp. doi:10.1016/j.patcog.2020.107569
García-Pedrajas, Nicolás (2009) Supervised projection approach for boosting classifiers. Pattern Recognition, 42 (9). 1742-1760 doi:10.1016/j.patcog.2008.12.023
Lu, Jiwen, Wang, Ruiping, Mian, Ajmal, Kumar, Ajay, Sarkar, Sudeep (2018) Distance metric learning for pattern recognition. Pattern Recognition, 75. 1-3 doi:10.1016/j.patcog.2017.10.032
Zhang, Yun Gang, Zhang, Chang Shui, Zhang, David (2004) Erratum to “Distance metric learning by knowledge embedding” [Pattern Recognition 37 (1) (2004) 161–163]. Pattern Recognition, 37 (4). 855pp. doi:10.1016/j.patcog.2003.12.001
Fernando, Basura, Fromont, Elisa, Muselet, Damien, Sebban, Marc (2012) Supervised learning of Gaussian mixture models for visual vocabulary generation. Pattern Recognition, 45 (2). 897-907 doi:10.1016/j.patcog.2011.07.021
 
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