A Robust and Adaptive Carrier Recovery Method for Chinese DTTB Receiver. - Weiqiang Liang; Jing Chai; Yunfeng Guan 001; Wenjun Zhang 001; Dazhi He (IEEE Trans. Broadcast., 2008)

Large Margin Feature Weighting Method via Linear Programming. - Bo Chen 001; Hongwei Liu 001; Jing Chai; Zheng Bao 001 (IEEE Trans. Knowl. Data Eng., 2009)

Generalized re-weighting local sampling mean discriminant analysis. - Jing Chai; Hongwei Liu 001; Zheng Bao 001 (Pattern Recognit., 2010)

Large margin nearest local mean classifier. - Jing Chai; Hongwei Liu 001; Bo Chen 001; Zheng Bao 001 (Signal Process., 2010)

Robust Positive semidefinite L-Isomap Ensemble. - Fanhua Shang; Licheng Jiao; Jiarong Shi; Jing Chai (Pattern Recognit. Lett., 2011)

Application of Frontal EEG Asymmetry to User Experience Research. - Jing Chai; Yan Ge; Yanfang Liu; Wen Li; Lei Zhou; Lin Yao; Xianghong Sun (HCI (23), 2014)

Using Physiological Measures to Evaluate User Experience of Mobile Applications. - Lin Yao; Yanfang Liu; Wen Li; Lei Zhou; Yan Ge; Jing Chai; Xianghong Sun (HCI (23), 2014)

Development and Application of a Chinese Webpage Suicide Information Mining System (Sims). - Penglai Chen; Jing Chai; Lu Zhang; Debin Wang (J. Medical Syst., 2014)

Maximum margin multiple-instance feature weighting. - Jing Chai; Hongtao Chen; Lixia Huang; Fanhua Shang (Pattern Recognit., 2014)

Multiple-instance discriminant analysis. - Jing Chai; Xinghao Ding; Hongtao Chen; Tingyu Li (Pattern Recognit., 2014)

Designing bag-level multiple-instance feature-weighting algorithms based on the large margin principle. - Jing Chai; Zehua Chen; Hongtao Chen; Xinghao Ding (Inf. Sci., 2016)

Compact Multiple-Instance Learning. - Jing Chai; Weiwei Liu 003; Ivor W. Tsang; Xiao-Bo Shen (CIKM, 2017)

Multiple-Instance feature extraction at the bag and instance levels using the maximum trace-difference criterion. - Jing Chai; Bo Chen 001; Fan Liu; Zehua Chen; Xinghao Ding (Inf. Sci., 2017)

Assessing the Difference in Measuring Bolt Stress: A Comparison of Two Optical Fiber Sensing Techniques. - Jing Chai; Qi Liu 004; Jinxuan Liu; Guihua Zhang; Dingding Zhang; Fengqi Qiu (J. Sensors, 2018)

基于Gossip协议的拜占庭共识算法 (Byzantine Consensus Algorithm Based on Gossip Protocol). - Shijiang Zhang; Jing Chai; Zehua Chen; Haiwu He (计算机科学, 2018)

Experimental Study on the Application of BOTDA in the Overlying Strata Deformation Monitoring Induced by Coal Mining. - Jing Chai; Wengang Du (J. Sensors, 2019)

Experimental Study on Overburden Deformation Evolution under Mining Effect Based on Fiber Bragg Grating Sensing Technology. - Wulin Lei; Jing Chai; Dingding Zhang; Yibo Ouyang; Zhe Ma; Wengang Du; Yongliang Liu (J. Sensors, 2020)

The Characterization Pattern of Overburden Deformation with Distributed Optical Fiber Sensing: An Analogue Model Test and Extensional Analysis. - Qiang Yuan; Jing Chai; Yiwei Ren; Yongliang Liu (Sensors, 2020)

Large Margin Partial Label Machine. - Jing Chai; Ivor W. Tsang; Weijie Chen 001 (IEEE Trans. Neural Networks Learn. Syst., 2020)

Chinese UMUX: Cross-Cultural Adaptation for Perceived Usability Measurement. - Yuhui Wang; Jing Chai; Tian Lei (Int. J. Hum. Comput. Interact., 2021)

Wavelength Characteristic Analysis of a FBG Array Embedded in Quaternary Unconsolidated Strata during a Deep Borehole Installation. - Dingding Zhang; Chenyang Ma; Yanyan Duan; Wengang Du; Jinxuan Liu; Jing Chai (J. Sensors, 2021)

Mine MIMO Depth Receiver: An Intelligent Receiving Model Based on Densely Connected Convolutional Networks. - Mingbo Wang; Anyi Wang; Zhaoyang Liu; Heng Zhang; Jing Chai (Sensors, 2021)

Investigation of Deformation Pattern and Movement Law of the Huge-Thick Conglomerate Stratum by a Large-Scale 3D Model Test with Distributed Optical Fiber Sensor Monitoring. - Qiang Yuan; Jing Chai; Yuzhu Zhang; Yongliang Liu; Yiwei Ren (Sensors, 2021)

Study on Quantitative Characterization of Coupling Effect between Mining-Induced Coal-Rock Mass and Optical Fiber Sensing. - Wengang Du; Jing Chai; Dingding Zhang; Yibo Ouyang; Yongliang Liu (Sensors, 2022)

Learning With Label Proportions by Incorporating Unmarked Data. - Jing Chai; Ivor W. Tsang (IEEE Trans. Neural Networks Learn. Syst., 2022)

Label Confidence Based Ensemble Partial Label Learning. - Xianran Sun; Jing Chai (CCIS, 2023)

Research on Similarity Simulation Experiment of Mine Pressure Appearance in Surface Gully Working Face Based on BOTDA. - Dingding Zhang; Zhiming Huang 010; Zhe Ma; Jianfeng Yang; Jing Chai (Sensors, 2023)

Random forest feature selection for partial label learning. - Xianran Sun; Jing Chai (Neurocomputing, 2023)

Learning with Label Proportions Based on Adaptive Confidence and Instance Similarity. - Jiale Wan; Jing Chai (ICKG, 2024)

Confidence-Driven Semi-Supervised Partial Label Learning. - Chengkun Liu; Jun Zhang; Jing Chai (IJCNN, 2024)

Partial label learning via weighted centroid clustering disambiguation. - Yuhang Tian; Xin Niu; Jing Chai (Neurocomputing, 2024)

Evolution Characteristics of Void in the Caving Zone Using Fiber Optic Sensing. - Jing Chai; Fengqi Qiu; Lei Zhu; Dingding Zhang (Sensors, 2024)

Overview of Health-Monitoring Technology for Long-Distance Transportation Pipeline and Progress in DAS Technology Application. - Yuyi Wu; Lei Gao; Jing Chai; Zhi Li; Chenyang Ma; Fengqi Qiu; Qiang Yuan; Dingding Zhang (Sensors, 2024)

Multi-view 3D Object Detection by Using a Preluded 2D Detector. - Songyan Liu; Tong Xiao; Chaoyi Luo; Jing Chai; Xiaofei Liu (ICIC (1), 2025)

Learning With Partial-Label and Unlabeled Data: Contrastive With Negative Example Separation. - Bangfa Jiang; Chengkun Liu; Jing Chai (IEEE Access, 2025)

Structured insight: an innovative disambiguation paradigm for semi-supervised partial label learning. - Xin Niu; Jing Chai; Musaed A. Alhussein; Khursheed Aurangzeb (J. King Saud Univ. Comput. Inf. Sci., 2025)