A Hierarchical Clustering for Categorical Data Based on Holo-Entropy. - Haojun Sun; Rongbo Chen; Shulin Jin; Yong Qin 002 (IEEE WISA, 2015)

Holo-Entropy Based Categorical Data Hierarchical Clustering. - Haojun Sun; Rongbo Chen; Yong Qin 002; Shengrui Wang (Informatica, 2017)

A Variable-Order Regime Switching Model to Identify Significant Patterns in Financial Markets. - Philippe Chatigny; Rongbo Chen; Jean-Marc Patenaude; Shengrui Wang (ICDM, 2018)

Time-Dependent Survival Neural Network for Remaining Useful Life Prediction. - Jianfei Zhang 002; Shengrui Wang; Lifei Chen; Gongde Guo; Rongbo Chen; Alain Vanasse (PAKDD (1), 2019)

Survival neural networks for time-to-event prediction in longitudinal study. - Jianfei Zhang 002; Lifei Chen; Yanfang Ye 001; Gongde Guo; Rongbo Chen; Alain Vanasse; Shengrui Wang (Knowl. Inf. Syst., 2020)

Dynamic order Markov model for categorical sequence clustering. - Rongbo Chen; Haojun Sun; Lifei Chen; Jianfei Zhang 002; Shengrui Wang (J. Big Data, 2021)

Dynamic Cross-sectional Regime Identification for Financial Market Prediction. - Rongbo Chen; Kunpeng Xu 002; Jean-Marc Patenaude; Shengrui Wang (COMPSAC, 2022)

Clustering-Based Cross-Sectional Regime Identification for Financial Market Forecasting. - Rongbo Chen; Mingxuan Sun; Kunpeng Xu 002; Jean-Marc Patenaude; Shengrui Wang (DEXA (2), 2022)

Unsupervised Learning via Graph Convolutional Network for Stock Trend Prediction. - Mingxuan Sun; Rongbo Chen; Jianfei Zhang 002; Shengrui Wang (AINA (1), 2023)