[1]Liang Bai, Jiye Liang, Fuyuan Cao. Semi-supervised clustering with constraints of different types from multiple information sources. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(9): 3247-3258.
[2]Liqin Yu,Fuyuan Cao, Xiao-ZhiGao,Jing Liu,Jiye Liang, k-Mnv-Rep: a k-type clustering algorithm for matrix-object data, Information Sciences, 2021,542:40-57.
[3]Xingwang Zhao, Jiye Liang, Jie Wang. A community detection algorithm based on graph compression for large-scale social networks. Information Sciences, 2021, 551: 358-372.
[4]Kaixuan Yao, Feilong Cao, Yee Leung, Jiye Liang. Deep neural network compression through interpretability-based filter pruning. Pattern Recognition, 2021, 119: 108056.
[5]Jie Wang, Jianqing Liang, Junbiao Cui, Jiye Liang. Semi-supervised learning with mixed-order graph convolutional networks. Information Sciences, 2021, 573: 171-181.
[6]Chuanjun Zhao, Suge Wang, Deyu Li. Cross-domain sentiment classification via parameter transferring and attention sharing mechanism. Information Sciences, 2021, 578: 281-296.
[7]JianxingZheng,QinwenLi, JianLiao. Heterogeneous type-specific entity representation learning for recommendations in e-commerce network. Information Processing and Management, 2021, 58: 102629.
[8]Hongye Tan, Xiaoyue Wang, Yu Ji and Ru Li et al. GCRC: A new challenging MRC dataset from Gaokao Chinese for explainable evaluation. In Findings of the Association for Computational Linguistics (ACL), 2021, pp. 1319-1330.
[9]Xuefeng Su, Ru Li, Xiaoli Li, et al. A knowledge-guided framework for frame identification. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistic (ACL), 2021, pp.5230–5240.
[10]冯晨娇, 宋鹏, 梁吉业. 一种基于3因素概率图模型的长尾推荐方法. 计算机研究与发展, 2021, 58(9): 1975-1986.