Yale Chang

According to our database, Yale Chang authored at least 21 papers between 2016 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

Multi-Task Prediction of Murmur and Outcome from Heart Sound Recordings.

Yale Chang, Luoluo Liu, Corneliu Antonescu

Proceedings of the Computing in Cardiology, 2022

2021

Utilizing machine learning to improve clinical trial design for acute respiratory distress syndrome.

Emma H. Schwager, Katharina Jansson, Asif Rahman, S. Schiffer, Yale Chang, Gregory Boverman, Brian Gross, Minnan Xu-Wilson, P. Boehme, Hubert Truebel, Joseph J. Frassica

npj Digit. Medicine, 2021

Interpretable Additive Recurrent Neural Networks For Multivariate Clinical Time Series.

Asif Rahman, Yale Chang, Jonathan Rubin

CoRR, 2021

Convolution-Free Waveform Transformers for Multi-Lead ECG Classification.

Annamalai Natarajan, Gregory Boverman, Yale Chang, Corneliu Antonescu, Jonathan Rubin

Proceedings of the Computing in Cardiology, CinC 2021, Brno, 2021

2020

Phenotyping with Prior Knowledge using Patient Similarity.

Asif Rahman, Yale Chang, Bryan Conroy, Minnan Xu-Wilson

Proceedings of the Machine Learning for Healthcare Conference, 2020

Shapelet Discovery for Atrial Fibrillation Detection.

Saman Parvaneh, Yale Chang

Proceedings of the Computing in Cardiology, 2020

A Wide and Deep Transformer Neural Network for 12-Lead ECG Classification.

Annamalai Natarajan, Yale Chang, Sara Mariani, Asif Rahman, Gregory Boverman, Shruti Vij, Jonathan Rubin

Proceedings of the Computing in Cardiology, 2020

2019

Spectral Non-Convex Optimization for Dimension Reduction with Hilbert-Schmidt Independence Criterion.

Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy

CoRR, 2019

Solving Interpretable Kernel Dimension Reduction.

Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy

CoRR, 2019

Deep Kernel Learning for Clustering.

Chieh Wu, Zulqarnain Khan, Yale Chang, Stratis Ioannidis, Jennifer G. Dy

CoRR, 2019

Solving Interpretable Kernel Dimensionality Reduction.

Chieh Wu, Jared Miller, Yale Chang, Mario Sznaier, Jennifer G. Dy

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

A Multi-Task Imputation and Classification Neural Architecture for Early Prediction of Sepsis from Multivariate Clinical Time Series.

Yale Chang, Jonathan Rubin, Gregory Boverman, Shruti Vij, Asif Rahman, Annamalai Natarajan, Saman Parvaneh

Proceedings of the 46th Computing in Cardiology, 2019

2018

Crowdclustering with Partition Labels.

Junxiang Chen, Yale Chang, Peter J. Castaldi, Michael H. Cho, Brian Hobbs, Jennifer G. Dy

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

A Bayesian Nonparametric Model for Disease Subtyping: Application to Emphysema Phenotypes.

James C. Ross, Peter J. Castaldi, Michael H. Cho, Junxiang Chen, Yale Chang, Jennifer G. Dy, Edwin K. Silverman, George R. Washko, Raúl San José Estépar

IEEE Trans. Medical Imaging, 2017

A Robust-Equitable Measure for Feature Ranking and Selection.

A. Adam Ding, Jennifer G. Dy, Yi Li, Yale Chang

J. Mach. Learn. Res., 2017

Clustering with Domain-Specific Usefulness Scores.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Multiple Clustering Views from Multiple Uncertain Experts.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 34th International Conference on Machine Learning, 2017

Clustering from Multiple Uncertain Experts.

Yale Chang, Junxiang Chen, Michael H. Cho, Peter J. Castaldi, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

Informative Subspace Learning for Counterfactual Inference.

Yale Chang, Jennifer G. Dy

Proceedings of the Thirty-First AAAI Conference on Artificial Intelligence, 2017

2016

Interpretable Clustering via Discriminative Rectangle Mixture Model.

Junxiang Chen, Yale Chang, Brian Hobbs, Peter J. Castaldi, Michael H. Cho, Edwin K. Silverman, Jennifer G. Dy

Proceedings of the IEEE 16th International Conference on Data Mining, 2016

A Robust-Equitable Copula Dependence Measure for Feature Selection.

Yale Chang, Yi Li, A. Adam Ding, Jennifer G. Dy

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, 2016