Cluster analysis in the COPDGene study identifies subtypes of smokers with distinct patterns of airway disease and emphysema PJ Castaldi, J Dy, J Ross, Y Chang, GR Washko, D Curran-Everett, ... Thorax 69 (5), 416-423, 2014 | 138 | 2014 |
Emotion fingerprints or emotion populations? A meta-analytic investigation of autonomic features of emotion categories. EH Siegel, MK Sands, W Van den Noortgate, P Condon, Y Chang, J Dy, ... Psychological bulletin 144 (4), 343, 2018 | 137 | 2018 |
Phenotypic and genetic heterogeneity among subjects with mild airflow obstruction in COPDGene JH Lee, MH Cho, MLN McDonald, CP Hersh, PJ Castaldi, JD Crapo, ... Respiratory medicine 108 (10), 1469-1480, 2014 | 27 | 2014 |
COPD subtypes identified by network-based clustering of blood gene expression Y Chang, K Glass, YY Liu, EK Silverman, JD Crapo, R Tal-Singer, ... Genomics 107 (2-3), 51-58, 2016 | 24 | 2016 |
Lobar emphysema distribution is associated with 5-year radiological disease progression A Boueiz, Y Chang, MH Cho, GR Washko, RSJ Estépar, RP Bowler, ... Chest 153 (1), 65-76, 2018 | 23 | 2018 |
A Bayesian nonparametric model for disease subtyping: application to emphysema phenotypes JC Ross, PJ Castaldi, MH Cho, J Chen, Y Chang, JG Dy, EK Silverman, ... IEEE transactions on medical imaging 36 (1), 343-354, 2016 | 16 | 2016 |
A Robust-Equitable Copula Dependence Measure for Feature Selection Y Chang, Y Li, A Ding, J Dy The 19th International Conference on Artificial Intelligence and Statistics …, 2016 | 15 | 2016 |
Interpretable clustering via discriminative rectangle mixture model J Chen, Y Chang, B Hobbs, P Castaldi, M Cho, E Silverman, J Dy 2016 IEEE 16th International Conference on Data Mining (ICDM), 823-828, 2016 | 12 | 2016 |
Informative subspace learning for counterfactual inference Y Chang, J Dy Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 11 | 2017 |
Multiple clustering views from multiple uncertain experts Y Chang, J Chen, MH Cho, PJ Castaldi, EK Silverman, JG Dy International Conference on Machine Learning, 674-683, 2017 | 8 | 2017 |
Clustering with domain-specific usefulness scores Y Chang, J Chen, MH Cho, PJ Castaidi, EK Silverman, JG Dy Proceedings of the 2017 SIAM International Conference on Data Mining, 207-215, 2017 | 7 | 2017 |
A robust-equitable measure for feature ranking and selection AA Ding, JG Dy, Y Li, Y Chang The Journal of Machine Learning Research 18 (1), 2394-2439, 2017 | 7 | 2017 |
Clustering from multiple uncertain experts Y Chang, J Chen, M Cho, P Castaldi, E Silverman, J Dy Artificial Intelligence and Statistics, 28-36, 2017 | 5 | 2017 |
Emotion fingerprints or emotion populations EH Siegel, MK Sands, P Condon, Y Chang, J Dy, KS Quigley, LF Barrett A meta-analytic investigation of autonomic features of emotion categories …, 0 | 5 | |
Solving interpretable kernel dimensionality reduction C Wu, J Miller, M Sznaier, J Dy Advances in Neural Information Processing Systems 32 (NIPS 2019) 32, 2019 | 3 | 2019 |
Solving interpretable kernel dimension reduction C Wu, J Miller, Y Chang, M Sznaier, J Dy arXiv preprint arXiv:1909.03093, 2019 | 3 | 2019 |
Crowdclustering with partition labels J Chen, Y Chang, P Castaldi, M Cho, B Hobbs, J Dy International Conference on Artificial Intelligence and Statistics, 1127-1136, 2018 | 3 | 2018 |
A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series Y Chang, J Rubin, G Boverman, S Vij, A Rahman, A Natarajan, ... International Conference in Computing in Cardiology 46, 2019 | 2 | 2019 |
Phenotyping with Prior Knowledge using Patient Similarity A Rahman, Y Chang, B Conroy, M Xu-Wilson Machine Learning for Healthcare Conference, 331-351, 2020 | 1 | 2020 |
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion C Wu, J Miller, Y Chang, M Sznaier, J Dy arXiv preprint arXiv:1909.05097, 2019 | 1 | 2019 |