Knowledge-Guided Bayesian Support Vector Machine for High-Dimensional Data with Application to Analysis of Genomics Data. - Wenli Sun; Changgee Chang; Yize Zhao; Qi Long (IEEE BigData, 2018)

Generalized Bayesian Factor Analysis for Integrative Clustering with Applications to Multi-Omics Data. - Eun Jeong Min; Changgee Chang; Qi Long (DSAA, 2018)

Bayesian Non-linear Support Vector Machine for High-Dimensional Data with Incorporation of Graph Information on Features. - Wenli Sun; Changgee Chang; Qi Long (IEEE BigData, 2019)

Knowledge-Guided Biclustering via Sparse Variational EM Algorithm. - Changgee Chang; Eun Jeong Min; Jihwan Oh; Qi Long (ICBK, 2019)

Joint Bayesian Variable Selection and Graph Estimation for Non-linear SVM with Application to Genomics Data. - Wenli Sun; Changgee Chang; Qi Long (DSAA, 2020)

GRIA: Graphical Regularization for Integrative Analysis. - Changgee Chang; Jihwan Oh; Qi Long (SDM, 2020)

Graph-guided Bayesian SVM with Adaptive Structured Shrinkage Prior for High-dimensional Data. - Wenli Sun; Changgee Chang; Qi Long (IEEE BigData, 2021)

Integrative analysis of multi-omics and imaging data with incorporation of biological information via structural Bayesian factor analysis. - Jingxuan Bao; Changgee Chang; Qiyiwen Zhang; Andrew J. Saykin; Li Shen 001; Qi Long (Briefings Bioinform., 2023)

Integrative learning of structured high-dimensional data from multiple datasets. - Changgee Chang; Zongyu Dai; Jihwan Oh; Qi Long (Stat. Anal. Data Min., 2023)

Robust knowledge-guided biclustering for multi-omics data. - Qiyiwen Zhang; Changgee Chang; Qi Long (Briefings Bioinform., 2023)