Shuai Huang

Orcid: 0000-0003-3054-5629

Affiliations:
  • University of Washington, Department of Industry & Systems Engineering, Seattle, WA, USA
  • Arizona State University, Tempe, AZ, USA (PhD 2012)


According to our database1, Shuai Huang authored at least 51 papers between 2009 and 2023.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2023
Sensitivity Analysis of Genome-Scale Metabolic Flux Prediction.
J. Comput. Biol., July, 2023

Efficient Optimal Power Flow Flexibility Assessment: A Machine Learning Approach.
Proceedings of the IEEE Power & Energy Society Innovative Smart Grid Technologies Conference, 2023

2022
A Learning Framework for Personalized Random Utility Maximization (RUM) Modeling of User Behavior.
IEEE Trans Autom. Sci. Eng., 2022

Density-Aware Personalized Training for Risk Prediction in Imbalanced Medical Data.
Proceedings of the Machine Learning for Healthcare Conference, 2022

VariGrow: Variational Architecture Growing for Task-Agnostic Continual Learning based on Bayesian Novelty.
Proceedings of the International Conference on Machine Learning, 2022

Dynimp: Dynamic Imputation for Wearable Sensing Data through Sensory and Temporal Relatedness.
Proceedings of the IEEE International Conference on Acoustics, 2022

VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Privacy-Preserving Cost-Sensitive Learning.
IEEE Trans. Neural Networks Learn. Syst., 2021

Semi-Supervised Topological Analysis for Elucidating Hidden Structures in High-Dimensional Transcriptome Datasets.
IEEE ACM Trans. Comput. Biol. Bioinform., 2021

Penalized Cox's proportional hazards model for high-dimensional survival data with grouped predictors.
Stat. Comput., 2021

Understanding the complexity of sepsis mortality prediction via rule discovery and analysis: a pilot study.
BMC Medical Informatics Decis. Mak., 2021

Risk Factor Identification in Heterogeneous Disease Progression with L1-Regularized Multi-state Models.
J. Heal. Informatics Res., 2021

SURVFIT: Doubly sparse rule learning for survival data.
J. Biomed. Informatics, 2021

Sparse Gated Mixture-of-Experts to Separate and Interpret Patient Heterogeneity in EHR data.
Proceedings of the IEEE EMBS International Conference on Biomedical and Health Informatics, 2021

Personalized Learning using Multiple Kernel Models.
Proceedings of the Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, 2021

2020
GPSRL: Learning Semi-Parametric Bayesian Survival Rule Lists from Heterogeneous Patient Data.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

Uncertainty Quantification for Deep Context-Aware Mobile Activity Recognition and Unknown Context Discovery.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019
A Robust AUC Maximization Framework With Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification.
IEEE Trans. Neural Networks Learn. Syst., 2019

Dynamic Inspection of Latent Variables in State-Space Systems.
IEEE Trans Autom. Sci. Eng., 2019

Early detection and risk assessment for chronic disease with irregular longitudinal data analysis.
J. Biomed. Informatics, 2019

Multi-stage optimization models for individual consistency and group consensus with preference relations.
Eur. J. Oper. Res., 2019

UQ-CHI: An Uncertainty Quantification-Based Contemporaneous Health Index for Degenerative Disease Monitoring.
CoRR, 2019

Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Collaborative Learning Framework for Estimating Many Individualized Regression Models in a Heterogeneous Population.
IEEE Trans. Reliab., 2018

Optimal Expert Knowledge Elicitation for Bayesian Network Structure Identification.
IEEE Trans Autom. Sci. Eng., 2018

Safe Feature Screening for Generalized LASSO.
IEEE Trans. Pattern Anal. Mach. Intell., 2018

Switching-State Dynamical Modeling of Daily Behavioral Data.
J. Heal. Informatics Res., 2018

DL-CHI: a dictionary learning-based contemporaneous health index for degenerative disease monitoring.
EURASIP J. Adv. Signal Process., 2018

Safe Active Feature Selection for Sparse Learning.
CoRR, 2018

A Robust AUC Maximization Framework with Simultaneous Outlier Detection and Feature Selection for Positive-Unlabeled Classification.
CoRR, 2018

Predicting Depression Severity by Multi-Modal Feature Engineering and Fusion.
Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence, 2018

2017
Unsupervised Sequential Outlier Detection With Deep Architectures.
IEEE Trans. Image Process., 2017

Functional Graphical Models for Manufacturing Process Modeling.
IEEE Trans Autom. Sci. Eng., 2017

Prognostics of surgical site infections using dynamic health data.
J. Biomed. Informatics, 2017

CHI: A contemporaneous health index for degenerative disease monitoring using longitudinal measurements.
J. Biomed. Informatics, 2017

Pruning Decision Trees via Max-Heap Projection.
Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Doubly Sparsifying Network.
Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, 2017

Transformed Anti-Sparse Hashing.
Proceedings of the British Machine Vision Conference 2017, 2017

Robust emotion recognition from low quality and low bit rate video: A deep learning approach.
Proceedings of the Seventh International Conference on Affective Computing and Intelligent Interaction, 2017

2016
Integration of Data Fusion Methodology and Degradation Modeling Process to Improve Prognostics.
IEEE Trans Autom. Sci. Eng., 2016

Heterogeneous multimodal biomarkers analysis for Alzheimer's disease via Bayesian network.
EURASIP J. Bioinform. Syst. Biol., 2016

On Benefits of Selection Diversity via Bilevel Exclusive Sparsity.
Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015
Domain-Knowledge Driven Cognitive Degradation Modeling for Alzheimer's Disease.
Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

A Scalable Algorithm for Structured Kernel Feature Selection.
Proceedings of the Eighteenth International Conference on Artificial Intelligence and Statistics, 2015

2013
A Sparse Structure Learning Algorithm for Gaussian Bayesian Network Identification from High-Dimensional Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2013

2012
Novel Statistical Models for Complex Data Structures.
PhD thesis, 2012

2011
Identifying Alzheimer's Disease-Related Brain Regions from Multi-Modality Neuroimaging Data using Sparse Composite Linear Discrimination Analysis.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

Brain effective connectivity modeling for alzheimer's disease by sparse gaussian bayesian network.
Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

2010
A Graphical Technique and Penalized Likelihood Method for Identifying and Estimating Infant Failures.
IEEE Trans. Reliab., 2010

Learning brain connectivity of Alzheimer's disease by sparse inverse covariance estimation.
NeuroImage, 2010

2009
Learning Brain Connectivity of Alzheimer's Disease from Neuroimaging Data.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009


  Loading...