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Yale Chang
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2020 – today
- 2022
- [c14]Yale Chang, Luoluo Liu, Corneliu Antonescu:
Multi-Task Prediction of Murmur and Outcome from Heart Sound Recordings. CinC 2022: 1-4 - 2021
- [j3]Emma H. Schwager
, Katharina Jansson
Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome. npj Digit. Medicine 4 (2021) - [c13]Annamalai Natarajan, Gregory Boverman, Yale Chang, Corneliu Antonescu, Jonathan Rubin:
Convolution-Free Waveform Transformers for Multi-Lead ECG Classification. CinC 2021: 1-4 - [i5]Asif Rahman, Yale Chang, Jonathan Rubin:
Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series. CoRR abs/2109.07602 (2021) - [i4]Annamalai Natarajan, Gregory Boverman, Yale Chang, Corneliu Antonescu, Jonathan Rubin:
Convolution-Free Waveform Transformers for Multi-Lead ECG Classification. CoRR abs/2109.15129 (2021) - 2020
- [c12]Annamalai Natarajan, Yale Chang, Sara Mariani, Asif Rahman, Gregory Boverman, Shruti Vij, Jonathan Rubin:
A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification. CinC 2020: 1-4 - [c11]Saman Parvaneh, Yale Chang:
Shapelet Discovery for Atrial Fibrillation Detection. CinC 2020: 1-4 - [c10]Asif Rahman, Yale Chang, Bryan Conroy, Minnan Xu-Wilson:
Phenotyping with Prior Knowledge using Patient Similarity. MLHC 2020: 331-351
2010 – 2019
- 2019
- [c9]Yale Chang, Jonathan Rubin, Gregory Boverman
A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series. CinC 2019: 1-4 - [c8]Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy:
Solving Interpretable Kernel Dimensionality Reduction. NeurIPS 2019: 7913-7923 - [i3]Chieh Wu, Zulqarnain Khan, Yale Chang, Stratis Ioannidis, Jennifer G. Dy:
Deep Kernel Learning for Clustering. CoRR abs/1908.03515 (2019) - [i2]Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy:
Solving Interpretable Kernel Dimension Reduction. CoRR abs/1909.03093 (2019) - [i1]Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy:
Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion. CoRR abs/1909.05097 (2019) - 2018
- [c7]Junxiang Chen, Yale Chang, Peter J. Castaldi, Michael H. Cho, Brian Hobbs, Jennifer G. Dy:
Crowdclustering with Partition Labels. AISTATS 2018: 1127-1136 - 2017
- [j2]A. Adam Ding, Jennifer G. Dy, Yi Li, Yale Chang:
A Robust-Equitable Measure for Feature Ranking and Selection. J. Mach. Learn. Res. 18: 71:1-71:46 (2017) - [j1]James C. Ross
A Bayesian Nonparametric Model for Disease Subtyping: Application to Emphysema Phenotypes. IEEE Trans. Medical Imaging 36(1): 343-354 (2017) - [c6]Yale Chang, Jennifer G. Dy:
Informative Subspace Learning for Counterfactual Inference. AAAI 2017: 1770-1776 - [c5]Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy:
Clustering from Multiple Uncertain Experts. AISTATS 2017: 28-36 - [c4]Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy:
Multiple Clustering Views from Multiple Uncertain Experts. ICML 2017: 674-683 - [c3]Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy:
Clustering with Domain-Specific Usefulness Scores. SDM 2017: 207-215 - 2016
- [c2]Yale Chang, Yi Li, A. Adam Ding, Jennifer G. Dy:
A Robust-Equitable Copula Dependence Measure for Feature Selection. AISTATS 2016: 84-92 - [c1]Junxiang Chen, Yale Chang, Brian Hobbs, Peter J. Castaldi, Michael H. Cho, Edwin K. Silverman, Jennifer G. Dy:
Interpretable Clustering via Discriminative Rectangle Mixture Model. ICDM 2016: 823-828
Coauthor Index
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