We only list some representative publications (mainly includes CCF-A, IEEE Transactions and JCR-1) in recent years, the full publication lists can be founded in my google scholar.
2023
[1] F. Nie, J. Lu, D. Wu, R. Wang and X. Li, A Novel Normalized-Cut Solver with Nearest Neighbor Hierarchical Initialization, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023.
[2] R. Wang, P. Wang, D. Wu*, Z. Sun*, F. Nie and X. Li, Multi-view and Multi-order Structured Graph Learning, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023.
[3] P. Wang1, D. Wu1, R. Wang, F. Nie, Multi-view Graph Clustering via Efficient Global-Local Spectral Embedding Fusion, ACM MM, 2023.
2022
[1] F. Nie, D. Wu, R. Wang and X. Li, Truncated Robust Principle Component Analysis with A General Optimization Framework, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022.
[2] D. Wu, F. Nie, J. Lu, R. Wang and X. Li, Effective Clustering via Structured Graph Learning, IEEE Transactions on Knowledge and Data Engineering (TKDE), 2022.
[3] D. Wu, X. Dong, J. Cao, R. Wang and F. Nie, Bidirectional Probabilistic Subspaces Approximation for Multi-view Clustering, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2022.
[4] D. Wu, H. Wang, Z. Hu and F. Nie, Improved Deep Metric Learning with Local Neighborhood Component Analysis, Information Sciences, 2022.
[5] D. Wu, X. Dong, F. Nie, R. Wang and X. Li, An Attention-based Framework for Multi-view Clustering on Grassmann Manifold, Pattern Recognition, 2022.
[6] D. Wu, C. Wei, J. Lu, F. Nie, R. Wang and X. Li, Adaptive-Order Proximity Learning for Graph-based Clustering, Pattern Recognition, 2022.
[7] D. Wu, J. Lu, F. Nie, R. Wang and Y. Yuan, EMGC2F: Efficient Multi-view Graph Clustering with Comprehensive Fusion, IJCAI, 2022.
2021
[1] D. Wu, J. Lu, F. Nie, R. Wang and X. Li, Balanced Graph Cut with Exponential Inter-Cluster Compactness, IEEE Transactions on Artificial Intelligence (TAI), 2021.
[2] D. Wu, F. Nie, X. Dong, R. Wang and X. Li, Parameter-Free Consensus Embedding Learning for Multi-View Graph-Based Clustering, IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2021.
[3] D. Wu, J. Xu, X. Dong, M. Liao, R. Wang, F. Nie and Y. Yuan, GSPL: A Succinct Kernel Model for Group-Sparse Subspaces Learning of Multiview Data, IJCAI, 2021.
