Yale Chang
Yale Chang
Philips Research North America
Verified email at ece.neu.edu - Homepage
Title
Cited by
Cited by
Year
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
1382014
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
1372018
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
272014
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
242016
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
232018
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
162016
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
152016
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
122016
Informative subspace learning for counterfactual inference
Y Chang, J Dy
Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017
112017
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
82017
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
72017
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
72017
Clustering from multiple uncertain experts
Y Chang, J Chen, M Cho, P Castaldi, E Silverman, J Dy
Artificial Intelligence and Statistics, 28-36, 2017
52017
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
32019
Solving interpretable kernel dimension reduction
C Wu, J Miller, Y Chang, M Sznaier, J Dy
arXiv preprint arXiv:1909.03093, 2019
32019
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
32018
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
22019
Phenotyping with Prior Knowledge using Patient Similarity
A Rahman, Y Chang, B Conroy, M Xu-Wilson
Machine Learning for Healthcare Conference, 331-351, 2020
12020
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
12019
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Articles 1–20