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Generative adversarial nets. In Advances in neural information processing systems. 2672--2680.  Ian Goodfellow Jean Pouget-Abadie Mehdi Mirza Bing Xu David Warde-Farley Sherjil Ozair Aaron Courville and Yoshua Bengio. 2014. Generative adversarial nets. In Advances in neural information processing systems. 2672--2680."},{"key":"e_1_3_2_1_11_1","volume-title":"Cluster analysis and clinical asthma phenotypes. American journal of respiratory and critical care medicine","author":"Haldar Pranab","year":"2008","unstructured":"Pranab Haldar , Ian D Pavord , Dominic E Shaw , Michael A Berry , Michael Thomas , Christopher E Brightling , Andrew J Wardlaw , and Ruth H Green . 2008. Cluster analysis and clinical asthma phenotypes. American journal of respiratory and critical care medicine , Vol. 178 , 3 ( 2008 ), 218--224. Pranab Haldar, Ian D Pavord, Dominic E Shaw, Michael A Berry, Michael Thomas, Christopher E Brightling, Andrew J Wardlaw, and Ruth H Green. 2008. 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Learning the parts of objects by non-negative matrix factorization . Nature , Vol. 401 , 6755 (1999), 788--791. Daniel D Lee and H Sebastian Seung. 1999. Learning the parts of objects by non-negative matrix factorization. Nature, Vol. 401, 6755 (1999), 788--791."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2885799"},{"key":"e_1_3_2_1_22_1","volume-title":"Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Machine learning","author":"Monti Stefano","year":"2003","unstructured":"Stefano Monti , Pablo Tamayo , Jill Mesirov , and Todd Golub . 2003. Consensus clustering: a resampling-based method for class discovery and visualization of gene expression microarray data. Machine learning , Vol. 52 , 1--2 ( 2003 ), 91--118. Stefano Monti, Pablo Tamayo, Jill Mesirov, and Todd Golub. 2003. 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EpiCentre, IVABS, Massey University (2009)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1093\/jpepsy\/jst076"},{"key":"e_1_3_2_1_32_1","volume-title":"Identifying Distinct Subgroups of Intensive Care Unit Patients: a Machine Learning Approach. Critical care medicine","author":"Vranas Kelly C","year":"2017","unstructured":"Kelly C Vranas , Jeffrey K Jopling , Timothy E Sweeney , Meghan C Ramsey , Arnold S Milstein , Christopher G Slatore , Gabriel J Escobar , and Vincent X Liu . 2017. Identifying Distinct Subgroups of Intensive Care Unit Patients: a Machine Learning Approach. Critical care medicine , Vol. 45 , 10 ( 2017 ), 1607. Kelly C Vranas, Jeffrey K Jopling, Timothy E Sweeney, Meghan C Ramsey, Arnold S Milstein, Christopher G Slatore, Gabriel J Escobar, and Vincent X Liu. 2017. Identifying Distinct Subgroups of Intensive Care Unit Patients: a Machine Learning Approach. 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