The Image Representation of Auricular Points Resistance Mapping. - Qin Gong; Xi Chen; Jinglei Liu (BMEI, 2009)

Model and Application of Optimal Coalition Structure. - Jinglei Liu; Wei Zhang; Lingling Wang (FSKD (4), 2009)

Representation and realization of binary-valued CP-nets in single-branch tree. - Xuejiao Sun; Jinglei Liu (FSKD, 2010)

An anytime algorithm for optimal coalition structure generation. - Zhenrong Zhang; Wei Zhang; Jinglei Liu (ICNC, 2010)

Joint estimation and compensation of transmitter and receiver IQ imbalances in millimeter-wave SC-FDE systems. - Xiantao Cheng; Zengqiang Luo; Jinglei Liu (ICC, 2015)

Expressive efficiency of two kinds of specific CP-nets. - Jinglei Liu; Shizhong Liao (Inf. Sci., 2015)

CP-nets的可满足性序列求解算法研究 (Research on Algorithm of Satisfiability Ranking Generation for CP-nets). - Xuejiao Sun; Jinglei Liu (计算机科学, 2015)

K*-Means: An Effective and Efficient K-Means Clustering Algorithm. - Jianpeng Qi; Yanwei Yu; Lihong Wang; Jinglei Liu (BDCloud-SocialCom-SustainCom, 2016)

Transfer Semi-Supervised Non-Negative Matrix Factorization for Speech Emotion Recognition. - Peng Song 002; Shifeng Ou; Xinran Zhang; Yun Jin; Wenming Zheng; Jinglei Liu; Yanwei Yu (IEICE Trans. Inf. Syst., 2016)

The Treewidth of Induced Graphs of Conditional Preference Networks Is Small. - Jie Liu; Jinglei Liu (Inf., 2016)

Cross-corpus speech emotion recognition based on transfer non-negative matrix factorization. - Peng Song 002; Wenming Zheng; Shifeng Ou; Xinran Zhang; Yun Jin; Jinglei Liu; Yanwei Yu (Speech Commun., 2016)

Operators of preference composition for CP-nets. - Xuejiao Sun; Jinglei Liu; Kai Wang 014 (Expert Syst. Appl., 2017)

Learning Corpus-Invariant Discriminant Feature Representations for Speech Emotion Recognition. - Peng Song 002; Shifeng Ou; Zhenbin Du; Yanyan Guo; Wenming Ma; Jinglei Liu; Wenming Zheng (IEICE Trans. Inf. Syst., 2017)

An effective and efficient hierarchical K-means clustering algorithm. - Jianpeng Qi; Yanwei Yu; Lihong Wang; Jinglei Liu; Yingjie Wang 002 (Int. J. Distributed Sens. Networks, 2017)

Learning CP-Nets Structure From Preference Data Streams. - Zhaowei Liu; Zhaolin Zhong; Chenghui Zhang; Yanwei Yu; Jinglei Liu (IEEE Access, 2018)

Region compatibility based stability assessment for decision trees. - Lihong Wang; Qiang Li; Yanwei Yu; Jinglei Liu (Expert Syst. Appl., 2018)

CP-nets学习的复杂度 (Complexity of CP-nets Learning). - Jinglei Liu; Shizhong Liao (计算机科学, 2018)

基于Nystrm采样和凸NMF的偏好聚类 (Preference Clustering Based on Nystrm Sampling and Convex-NMF). - Meijiao Yang; Jinglei Liu (计算机科学, 2018)

CP-Nets Structure Learning Based on mRMCR Principle. - Su Liu; Jinglei Liu (IEEE Access, 2019)

Efficient preference clustering via random fourier features. - Jingshu Liu; Li Wang; Jinglei Liu (Big Data Min. Anal., 2019)

Multiple Kernel Subspace Clustering Based on Consensus Hilbert Space and Second-Order Neighbors. - Zhongyuan Wang 003; Jinglei Liu (IEEE Access, 2020)

Adaptive Graph Regularized Low-Rank Matrix Factorization With Noise and Outliers for Clustering. - Min Zhao; Jinglei Liu (IEEE Access, 2020)

Top-K interesting preference rules mining based on MaxClique. - Zheng Tan; Hang Yu; Wei Wei; Jinglei Liu (Expert Syst. Appl., 2020)

Consensus kernel subspace clustering based on coefficient discriminant information. - Zhongyuan Wang; Jinglei Liu (Appl. Soft Comput., 2021)

Robust clustering with sparse corruption via ℓ2, 1, ℓ1 norm constraint and Laplacian regularization. - Min Zhao; Jinglei Liu (Expert Syst. Appl., 2021)

Bipartite Graph-based Discriminative Feature Learning for Multi-View Clustering. - Weiqing Yan; Jindong Xu; Jinglei Liu; Guanghui Yue 001; Chang Tang (ACM Multimedia, 2022)

Entropy Regularized Unsupervised Clustering Based on Maximum Correntropy Criterion and Adaptive Neighbors. - Xinyu Li; Hui Fan; Jinglei Liu (IEICE Trans. Inf. Syst., 2023)

Exemplar-based large-scale low-rank matrix decomposition for collaborative prediction. - Hengxin Lei; Jinglei Liu; Yong Yu (Int. J. Comput. Math., 2023)

One-step unsupervised clustering based on information theoretic metric and adaptive neighbor manifold regularization. - Xinyu Li; Hui Fan; Jinglei Liu (Eng. Appl. Artif. Intell., 2023)

Noise-aware clustering based on maximum correntropy criterion and adaptive graph regularization. - Xinyu Li; Hui Fan; Jinglei Liu (Inf. Sci., 2023)

Noise-tolerant clustering via joint doubly stochastic matrix regularization and dual sparse coding. - Zhaoqun Shi; Jinglei Liu (Expert Syst. Appl., 2023)

Image classification based on weighted nonconvex low-rank and discriminant least squares regression. - Kunyan Zhong; Jinglei Liu (Appl. Intell., 2023)

Large-Scale Gaussian Process Regression Based on Random Fourier Features and Local Approximation with Tsallis Entropy. - Hongli Zhang; Jinglei Liu (IEICE Trans. Inf. Syst., 2023)

One-step subspace clustering based on adaptive graph regularization and correntropy induced metric. - Yechao Cheng; Jinglei Liu (Appl. Intell., 2023)

Clustering by sparse orthogonal NMF and interpretable neural network. - Yongwei Gai; Jinglei Liu (Multim. Syst., 2023)

A 19.7 TFLOPS/W Multiply-less Logarithmic Floating-Point CIM Architecture with Error-Reduced Compensated Approximate Adder. - Mengjie Li; Hongyi Zhang; Siqi He; Haozhe Zhu; Hao Zhang; Jinglei Liu; Jiayuan Chen; Zhenping Hu; Xiaoyang Zeng; Chixiao Chen (ISCAS, 2024)

Join multiple Riemannian manifold representation and multi-kernel non-redundancy for image clustering. - Mengyuan Zhang; Jinglei Liu (CAAI Trans. Intell. Technol., 2024)

Joint contrastive self-supervised learning and weak-orthogonal product quantization for fast image retrieval. - Xusheng Zhao; Jinglei Liu (Knowl. Based Syst., 2024)

Similarity Learning for Land Use Scene-Level Change Detection. - Jinglei Liu; Weixun Zhou; Haiyan Guan; Wenzhi Zhao (IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2024)

Leveraging self-paced learning and deep sparse embedding for image clustering. - Yanming Liu; Jinglei Liu (Neural Comput. Appl., 2024)

Geometric Parameter Effects on Bandgap Characteristics of Periodic Pile Barriers in Passive Vibration Isolation. - Jinglei Liu; Xiuxin Li; Jinyuan Cao; Zhengchun Duan; Qingzhi Ye; Guishuai Feng (Symmetry, 2024)

Joint U-Nets with hierarchical graph structure and sparse Transformer for hyperspectral image classification. - Pengfei Zhu; Jinglei Liu (Expert Syst. Appl., 2025)

RM-BGNN: A weakly informative Bayesian graph neural network based on residual mechanism. - Jihao Dong; Zhaowei Liu; Dong Yang; Peng Song; Jinglei Liu; Anzuo Jiang (Neurocomputing, 2025)

Interpretable unsupervised neural network structure for data clustering via differentiable reconstruction of ONMF and sparse autoencoder. - Yongwei Gai; Jinglei Liu (Neural Networks, 2025)

Jointly stochastic fully symmetric interpolatory rules and local approximation for scalable Gaussian process regression. - Hongli Zhang; Jinglei Liu (Pattern Recognit., 2025)

Graph convolutional and random Fourier feature mapping for hyperspectral image clustering. - Xingyu Li; Jinglei Liu (J. Supercomput., 2025)

Leveraging variant of CAE with sparse convolutional embedding and two-stage application-driven data augmentation for image clustering. - Yanming Liu; Jinglei Liu (Soft Comput., 2025)