Transfer Learning for Survival Analysis via Efficient L2, 1-Norm Regularized Cox Regression. - Yan Li 052; Lu Wang 004; Jie Wang 005; Jieping Ye; Chandan K. Reddy (ICDM, 2016)

Poisson-Markov Mixture Model and Parallel Algorithm for Binning Massive and Heterogenous DNA Sequencing Reads. - Lu Wang 004; Dongxiao Zhu; Yan Li 052; Ming Dong 001 (ISBRA, 2016)

Multi-task Survival Analysis. - Lu Wang 004; Yan Li 052; Jiayu Zhou; Dongxiao Zhu; Jieping Ye (ICDM, 2017)

Modeling Over-Dispersion for Network Data Clustering. - Lu Wang 004; Dongxiao Zhu; Ming Dong 001; Yan Li 052 (ICMLA, 2017)

Transcriptome assembly strategies for precision medicine. - Lu Wang 004; Lipi R. Acharya; Changxin Bai; Dongxiao Zhu (Quant. Biol., 2017)

Obesity risk factors ranking using multi-task learning. - Lu Wang 004; Dongxiao Zhu; Elizabeth Towner; Ming Dong 001 (BHI, 2018)

Clustering over-dispersed data with mixed feature types. - Lu Wang 004; Dongxiao Zhu; Ming Dong 001 (Stat. Anal. Data Min., 2018)

Predicting Emergency Department Visits Based on Cancer Patient Types. - Mahsa Rouzbahman; Lu Wang 004; Mark H. Chignell; Leon Zucherman; Nipon Charoenkitkarn; Lisa Barbera (BIBM, 2019)

Tuning a Cancer Patient Typology Based on Emergency Department Visits. - Mahsa Rouzbahman; Lu Wang 004; Mark H. Chignell; Leon Zucherman; Nipon Charoenkitkarn; Lisa Barbera (BIBM, 2019)

Prioritization of Multi-Level Risk Factors for Obesity. - Lu Wang 004; Ming Dong 001; Elizabeth Towner; Dongxiao Zhu (BIBM, 2019)

Tackling Multiple Ordinal Regression Problems: Sparse and Deep Multi-Task Learning Approaches. - Lu Wang 004; Dongxiao Zhu (CoRR, 2019)

Multi-task learning based survival analysis for multi-source block-wise missing data. - Yan Li 052; Lu Wang 004; Jiayu Zhou; Jieping Ye (Neurocomputing, 2019)

Cluster-Boosted Multi-Task Learning Framework for Survival Analysis. - Lu Wang 004; Mark H. Chignell; Haoyan Jiang; Nipon Charoenkitkarn (BIBE, 2020)

Data Mining Methods for Optimizing Feature Extraction and Model Selection. - Masha Rouzbahman; Alexandra Jovicic; Lu Wang 004; Leon Zucherman; Zahid Abul-Basher; Nipon Charoenkitkarn; Mark H. Chignell (IAIT, 2020)

Interactive Machine Learning for Data Exfiltration Detection: Active Learning with Human Expertise. - Mu-Huan Chung; Mark H. Chignell; Lu Wang 004; Alexandra Jovicic; Abhay Raman (SMC, 2020)

Discovering the Causal Structure of the Hamilton Rating Scale for Depression Using Causal Discovery. - Lu Wang 004; Mark H. Chignell; Haoyan Jiang; Sachinthya Lokuge; Geneva Mason; Kathryn Fotinos; Martin Katzman (BHI, 2021)

Prioritization of Multi-level Risk Factors, and Predicting Changes in Depression Ratings after Treatment Using Multi-Task Learning. - Lu Wang 004; Mark H. Chignell; Haoyan Jiang; Sachinthya Lokuge; Geneva Mason; Kathryn Fotinos; Martin Katzman (BIBM, 2021)

Hierarchical Clustering of Multi-Study Depression Data Yields Four Symptom Clusters. - Lu Wang 004; Mark H. Chignell; Haoyan Jiang; Sachinthya Lokuge; Geneva Mason; Kathryn Fotinos; Martin Katzman (BIBM, 2021)

Combining Ranking and Point-wise Losses for Training Deep Survival Analysis Models. - Lu Wang 004; Yan Li; Mark H. Chignell (ICDM, 2021)

MD-MTL: An Ensemble Med-Multi-Task Learning Package for DiseaseScores Prediction and Multi-Level Risk Factor Analysis. - Lu Wang 004; Haoyan Jiang; Mark H. Chignell (CoRR, 2021)

Tackling ordinal regression problem for heterogeneous data: sparse and deep multi-task learning approaches. - Lu Wang 004; Dongxiao Zhu (Data Min. Knowl. Discov., 2021)

Poster: Binge drinking risk factors ranking using multi-task learning. - Daniel Gallegos; Elaine Raymond; Lu Wang 004 (MobiHoc, 2023)

Implementing Active Learning in Cybersecurity: Detecting Anomalies in Redacted Emails. - Mu-Huan Chung; Lu Wang 004; Sharon Li; Yuhong Yang 007; Calvin Giang; Khilan Jerath; Abhay Raman; David Lie; Mark H. Chignell (CoRR, 2023)

Implementing Data Exfiltration Defense in Situ: A Survey of Countermeasures and Human Involvement. - Mu-Huan Chung; Yuhong Yang 007; Lu Wang 004; Greg Cento; Khilan Jerath; Abhay Raman; David Lie; Mark H. Chignell (ACM Comput. Surv., 2023)

The Evolution of HCI and Human Factors: Integrating Human and Artificial Intelligence. - Mark H. Chignell; Lu Wang 004; Atefeh Zare; Jamy Li (ACM Trans. Comput. Hum. Interact., 2023)

Maximizing Information Gain in Privacy-Aware Active Learning of Email Anomalies. - Mu-Huan Chung; Sharon Li; Jaturong Kongmanee; Lu Wang 004; Yuhong Yang 007; Calvin Giang; Khilan Jerath; Abhay Raman; David Lie; Mark H. Chignell (CoRR, 2024)