Identification of Wireless User Perception Based on Unsupervised Machine Learning. - Kaixuan Zhang 003; Guanghui Fan; Jun Zeng 005; Guan Gui 001 (ADHIP (1), 2019)

Machine Learning Based Quantitative Association Rule Mining Method for Evaluating Cellular Network Performance. - Guanghui Fan; Wenjuan Shi; Liang Guo 003; Jun Zeng 005; Kaixuan Zhang 003; Guan Gui 001 (IEEE Access, 2019)

Cell Scene Division and Visualization Based on Autoencoder and K-Means Algorithm. - Jun Zeng 005; Juan Wang 008; Liang Guo 003; Guanghui Fan; Kaixuan Zhang 003; Guan Gui 001 (IEEE Access, 2019)

WeUp: Wireless User Perception Based on Dimensional Reduction and Semi-Supervised Clustering. - Kaixuan Zhang 003; Wenjuan Shi; Jun Zeng 005; Guanghui Fan; Yu Wang 078; Guan Gui 001 (IEEE Access, 2019)

Random Forest Algorithm-Based Lightweight Comprehensive Evaluation for Wireless User Perception. - Kaixuan Zhang 003; Juan Wang 008; Wei Zhang 122; Ke Wang 005; Jun Zeng 005; Guanghui Fan; Guan Gui 001 (IEEE Access, 2019)

Cellular Network Performance using Machine Learning based Quantitative Association Rule Mining Method. - Guanghui Fan; Juan Wang 008; Kaixuan Zhang 003; Jun Zeng 005; Guan Gui 001 (VTC Spring, 2020)

Lightweight Comprehensive Evaluation Method for Wireless User Perception Based on Random Forest. - Kaixuan Zhang 003; Guanghui Fan; Jun Zeng 005; Guan Gui 001 (VTC Spring, 2020)

Semi-Supervised Machine Learning Aided Anomaly Detection Method in Cellular Networks. - Yutao Lu; Juan Wang 008; Miao Liu 002; Kaixuan Zhang 003; Guan Gui 001; Tomoaki Ohtsuki; Fumiyuki Adachi (IEEE Trans. Veh. Technol., 2020)