Unsupervised Feature Learning for Human Activity Recognition Using Smartphone Sensors. - Yongmou Li; Dian-xi Shi; Bo Ding; Dongbo Liu (MIKE, 2014)

A Variable Markovian Based Outlier Detection Method for Multi-Dimensional Sequence over Data Stream. - Dongsheng Yang; Yijie Wang 001; Yongmou Li; Xingkong Ma (PDCAT, 2016)

A Distributed Class-Incremental Learning Method Based on Neural Network Parameter Fusion. - Hongtao Guan; Yijie Wang 001; Xingkong Ma; Yongmou Li (HPCC/SmartCity/DSS, 2019)

DCIGAN: A Distributed Class-Incremental Learning Method Based on Generative Adversarial Networks. - Hongtao Guan; Yijie Wang 001; Xingkong Ma; Yongmou Li (ISPA/BDCloud/SocialCom/SustainCom, 2019)

Improve the Detection of Clustered Outliers via Outlier Score Propagation. - Yongmou Li; Yijie Wang; Hongtao Guan (ISPA/BDCloud/SocialCom/SustainCom, 2019)

A Graph-Based Method for Active Outlier Detection With Limited Expert Feedback. - Yongmou Li; Yijie Wang 001; Xingkong Ma; Cheng Qian; Xiaoyong Li 002 (IEEE Access, 2019)

Variational autoencoder-based outlier detection for high-dimensional data. - Yongmou Li; Yijie Wang 001; Xingkong Ma (Intell. Data Anal., 2019)

FAAD: an unsupervised fast and accurate anomaly detection method for a multi-dimensional sequence over data stream. - Bin Li 030; Yijie Wang 001; Dongsheng Yang; Yongmou Li; Xingkong Ma (Frontiers Inf. Technol. Electron. Eng., 2019)