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Shuai Huang 0001
Person information
- affiliation: University of Washington, Department of Industry & Systems Engineering, Seattle, WA, USA
- affiliation (PhD 2012): Arizona State University, Tempe, AZ, USA
Other persons with the same name
- Shuai Huang — disambiguation page
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2020 – today
- 2023
- [j26]Puhua Niu
, Maria J. Soto, Shuai Huang, Byung-Jun Yoon, Edward R. Dougherty, Francis J. Alexander, Ian Blaby, Xiaoning Qian:
Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction. J. Comput. Biol. 30(7): 751-765 (2023) - [c21]Wengeng Pan, Chaoyue Zhao, Lei Fan, Shuai Huang:
Efficient Optimal Power Flow Flexibility Assessment: A Machine Learning Approach. ISGT 2023: 1-5 - 2022
- [j25]Jingshuo Feng
A Learning Framework for Personalized Random Utility Maximization (RUM) Modeling of User Behavior. IEEE Trans Autom. Sci. Eng. 19(1): 510-521 (2022) - [c20]Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian:
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. AISTATS 2022: 1359-1379 - [c19]Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi:
Dynimp: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporal Relatedness. ICASSP 2022: 3988-3992 - [c18]Randy Ardywibowo, Zepeng Huo, Zhangyang Wang, Bobak J. Mortazavi, Shuai Huang, Xiaoning Qian:
VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty. ICML 2022: 865-877 - [c17]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak J. Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. MLHC 2022: 101-122 - [i11]Randy Ardywibowo, Shahin Boluki, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition. CoRR abs/2204.00130 (2022) - [i10]Zepeng Huo, Xiaoning Qian, Shuai Huang, Zhangyang Wang, Bobak Mortazavi:
Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data. CoRR abs/2207.11382 (2022) - [i9]Zepeng Huo, Taowei Ji, Yifei Liang, Shuai Huang, Zhangyang Wang, Xiaoning Qian, Bobak Mortazavi:
DynImp: Dynamic Imputation for Wearable Sensing Data Through Sensory and Temporal Relatedness. CoRR abs/2209.15415 (2022) - 2021
- [j24]Ameer Hamza Shakur
SURVFIT: Doubly sparse rule learning for survival data. J. Biomed. Informatics 117: 103691 (2021) - [j23]Xuan Dang
Risk Factor Identification in Heterogeneous Disease Progression with L1-Regularized Multi-state Models. J. Heal. Informatics Res. 5(1): 20-53 (2021) - [j22]Ying Wu
Understanding the complexity of sepsis mortality prediction via rule discovery and analysis: a pilot study. BMC Medical Informatics Decis. Mak. 21(1): 334 (2021) - [j21]Xuan Dang
Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors. Stat. Comput. 31(6): 77 (2021) - [j20]Tianshu Feng
Semi-Supervised Topological Analysis for Elucidating Hidden Structures in High-Dimensional Transcriptome Datasets. IEEE ACM Trans. Comput. Biol. Bioinform. 18(4): 1620-1631 (2021) - [j19]Yi Yang, Shuai Huang
Privacy-Preserving Cost-Sensitive Learning. IEEE Trans. Neural Networks Learn. Syst. 32(5): 2105-2116 (2021) - [c16]Anthony Kuh, Shuai Huang, Cynthia Chen:
Personalized Learning using Multiple Kernel Models. APSIPA ASC 2021: 2085-2088 - [c15]Zepeng Huo, Lida Zhang, Rohan Khera, Shuai Huang, Xiaoning Qian, Zhangyang Wang, Bobak J. Mortazavi:
Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data. BHI 2021: 1-4 - 2020
- [c14]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. AISTATS 2020: 3894-3904 - [c13]Ameer Hamza Shakur
GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data. ICPR 2020: 10608-10615 - [i8]Zepeng Huo, Arash Pakbin, Xiaohan Chen, Nathan C. Hurley, Ye Yuan, Xiaoning Qian, Zhangyang Wang, Shuai Huang, Bobak Mortazavi:
Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery. CoRR abs/2003.01753 (2020)
2010 – 2019
- 2019
- [j18]Zhibin Wu
Multi-stage optimization models for individual consistency and group consensus with preference relations. Eur. J. Oper. Res. 275(1): 182-194 (2019) - [j17]Kai He
Early detection and risk assessment for chronic disease with irregular longitudinal data analysis. J. Biomed. Informatics 96 (2019) - [j16]Tianshu Feng
Dynamic Inspection of Latent Variables in State-Space Systems. IEEE Trans Autom. Sci. Eng. 16(3): 1232-1243 (2019) - [j15]Ke Ren
A Robust AUC Maximization Framework With Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification. IEEE Trans. Neural Networks Learn. Syst. 30(10): 3072-3083 (2019) - [c12]Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. AISTATS 2019: 266-275 - [i7]Randy Ardywibowo, Guang Zhao, Zhangyang Wang, Bobak Mortazavi, Shuai Huang, Xiaoning Qian:
Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models. CoRR abs/1901.02427 (2019) - [i6]Aven Samareh, Shuai Huang:
UQ-CHI: An Uncertainty Quantification-Based Contemporaneous Health Index for Degenerative Disease Monitoring. CoRR abs/1902.08246 (2019) - 2018
- [j14]Aven Samareh
DL-CHI: a dictionary learning-based contemporaneous health index for degenerative disease monitoring. EURASIP J. Adv. Signal Process. 2018: 17 (2018) - [j13]Randy Ardywibowo
Switching-State Dynamical Modeling of Daily Behavioral Data. J. Heal. Informatics Res. 2(3): 228-247 (2018) - [j12]Shaogang Ren
Safe Feature Screening for Generalized LASSO. IEEE Trans. Pattern Anal. Mach. Intell. 40(12): 2992-3006 (2018) - [j11]Cao Xiao, Yan Jin, Ji Liu, Bo Zeng, Shuai Huang
Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification. IEEE Trans Autom. Sci. Eng. 15(3): 1163-1177 (2018) - [j10]Ying Lin, Kaibo Liu
A Collaborative Learning Framework for Estimating Many Individualized Regression Models in a Heterogeneous Population. IEEE Trans. Reliab. 67(1): 328-341 (2018) - [c11]Aven Samareh, Yan Jin, Zhangyang Wang, Xiangyu Chang, Shuai Huang:
Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion. AAAI 2018: 8147-8148 - [i5]Ke Ren, Haichuan Yang, Yu Zhao, Mingshan Xue, Hongyu Miao, Shuai Huang, Ji Liu:
A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification. CoRR abs/1803.06604 (2018) - [i4]Shaogang Ren, Jianhua Z. Huang, Shuai Huang, Xiaoning Qian:
Safe Active Feature Selection for Sparse Learning. CoRR abs/1806.05817 (2018) - 2017
- [j9]Chuyang Ke, Yan Jin, Heather L. Evans
Prognostics of surgical site infections using dynamic health data. J. Biomed. Informatics 65: 22-33 (2017) - [j8]Yijun Huang, Qiang Meng, Heather L. Evans
CHI: A contemporaneous health index for degenerative disease monitoring using longitudinal measurements. J. Biomed. Informatics 73: 115-124 (2017) - [j7]Hongyue Sun
Functional Graphical Models for Manufacturing Process Modeling. IEEE Trans Autom. Sci. Eng. 14(4): 1612-1621 (2017) - [j6]Weining Lu
Unsupervised Sequential Outlier Detection With Deep Architectures. IEEE Trans. Image Process. 26(9): 4321-4330 (2017) - [c10]Bowen Cheng, Zhangyang Wang, Zhaobin Zhang, Zhu Li, Ding Liu
Robust emotion recognition from low quality and low bit rate video: A deep learning approach. ACII 2017: 65-70 - [c9]Zhangyang Wang, Ji Liu, Shuai Huang, Xinchao Wang, Shiyu Chang:
Transformed Anti-Sparse Hashing. BMVC 2017 - [c8]Zhangyang Wang, Shuai Huang, Jiayu Zhou, Thomas S. Huang:
Doubly Sparsifying Network. IJCAI 2017: 3020-3026 - [c7]Zhi Nie, Binbin Lin, Shuai Huang, Naren Ramakrishnan
Pruning Decision Trees via Max-Heap Projection. SDM 2017: 10-18 - [i3]Bowen Cheng, Zhangyang Wang, Zhaobin Zhang, Zhu Li, Ding Liu, Jianchao Yang, Shuai Huang, Thomas S. Huang:
Robust Emotion Recognition from Low Quality and Low Bit Rate Video: A Deep Learning Approach. CoRR abs/1709.03126 (2017) - [i2]Aven Samareh, Yan Jin, Zhangyang Wang, Xiangyu Chang, Shuai Huang:
Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion. CoRR abs/1711.11155 (2017) - 2016
- [j5]Yan Jin, Yi Su, Xiao-Hua Zhou
Heterogeneous multimodal biomarkers analysis for Alzheimer's disease via Bayesian network. EURASIP J. Bioinform. Syst. Biol. 2016: 12 (2016) - [j4]Kaibo Liu
Integration of Data Fusion Methodology and Degradation Modeling Process to Improve Prognostics. IEEE Trans Autom. Sci. Eng. 13(1): 344-354 (2016) - [c6]Haichuan Yang, Yijun Huang, Lam Tran, Ji Liu, Shuai Huang:
On Benefits of Selection Diversity via Bilevel Exclusive Sparsity. CVPR 2016: 5945-5954 - [i1]Chuyang Ke, Yan Jin, Heather L. Evans, Bill Lober, Xiaoning Qian, Ji Liu, Shuai Huang:
Prognostics of Surgical Site Infections using Dynamic Health Data. CoRR abs/1611.04049 (2016) - 2015
- [c5]Shaogang Ren, Shuai Huang, John A. Onofrey, Xenios Papademetris, Xiaoning Qian:
A Scalable Algorithm for Structured Kernel Feature Selection. AISTATS 2015 - [c4]Ying Lin, Kaibo Liu, Eunshin Byon, Xiaoning Qian, Shuai Huang:
Domain-Knowledge Driven Cognitive Degradation Modeling for Alzheimer's Disease. SDM 2015: 721-729 - 2013
- [j3]Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen
A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 35(6): 1328-1342 (2013) - 2012
- [b1]Shuai Huang:
Novel Statistical Models for Complex Data Structures. Arizona State University, Tempe, USA, 2012 - 2011
- [c3]Shuai Huang, Jing Li, Jieping Ye, Adam Fleisher, Kewei Chen
Brain effective connectivity modeling for alzheimer's disease by sparse gaussian bayesian network. KDD 2011: 931-939 - [c2]Shuai Huang, Jing Li, Jieping Ye, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman:
Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis. NIPS 2011: 1431-1439 - 2010
- [j2]Shuai Huang, Jing Li, Liang Sun, Jieping Ye, Adam Fleisher, Teresa Wu, Kewei Chen
Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation. NeuroImage 50(3): 935-949 (2010) - [j1]Shuai Huang, Rong Pan
A Graphical Technique and Penalized Likelihood Method for Identifying and Estimating Infant Failures. IEEE Trans. Reliab. 59(4): 650-660 (2010)
2000 – 2009
- 2009
- [c1]Shuai Huang, Jing Li, Liang Sun, Jun Liu, Teresa Wu, Kewei Chen, Adam Fleisher, Eric Reiman, Jieping Ye:
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data. NIPS 2009: 808-816
Coauthor Index
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