| -Laplacian Regularization for Scene Recognition W Liu, X Ma, Y Zhou, D Tao, J Cheng IEEE Transactions on Cybernetics 49 (8), 2927-2940, 2018 | 80 | 2018 |
| Hypergraph -Laplacian Regularization for Remotely Sensed Image Recognition X Ma, W Liu, S Li, D Tao, Y Zhou IEEE Transactions on Geoscience and Remote Sensing 57 (3), 1585-1595, 2018 | 60 | 2018 |
| Comprehensive graph gradual pruning for sparse training in graph neural networks C Liu, X Ma, Y Zhan, L Ding, D Tao, B Du, W Hu, DP Mandic IEEE Transactions on Neural Networks and Learning Systems, 2023 | 23 | 2023 |
| Ensemble p-Laplacian Regularization for Scene Image Recognition X Ma, W Liu, D Tao, Y Zhou Cognitive Computation 11, 841-854, 2019 | 17 | 2019 |
| Alpha-IoU: A family of power intersection over union losses for bounding box regression. arXiv 2021 J He, S Erfani, X Ma, J Bailey, Y Chi, XS Hua arXiv preprint arXiv:2110.13675, 0 | 16 | |
| Masked graph auto-encoder constrained graph pooling C Liu, Y Zhan, X Ma, D Tao, B Du, W Hu Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 8 | 2022 |
| Gapformer: Graph transformer with graph pooling for node classification C Liu, Y Zhan, X Ma, L Ding, D Tao, J Wu, W Hu Proceedings of the 32nd International Joint Conference on Artificial …, 2023 | 5 | 2023 |
| Effective human action recognition by combining manifold regularization and pairwise constraints X Ma, D Tao, W Liu Multimedia Tools and Applications 78, 13313-13329, 2019 | 5 | 2019 |
| Recent advances of manifold regularization X Ma, W Liu Manifolds II-Theory and Applications, 2018 | 5 | 2018 |
| Learning representation on optimized high-order manifold for visual classification X Ma, W Liu, Q Tian, Y Gao IEEE Transactions on Multimedia 24, 3989-4001, 2021 | 4 | 2021 |
| Graph structure reforming framework enhanced by commute time distance for graph classification W Yu, X Ma, J Bailey, Y Zhan, J Wu, B Du, W Hu Neural Networks 168, 539-548, 2023 | 1 | 2023 |
| Exploring sparsity in graph transformers C Liu, Y Zhan, X Ma, L Ding, D Tao, J Wu, W Hu, B Du Neural Networks, 106265, 2024 | | 2024 |
| Training Sparse Graph Neural Networks via Pruning and Sprouting X Ma, X Ma, S Erfani, J Bailey Proceedings of the 2024 SIAM International Conference on Data Mining (SDM …, 2024 | | 2024 |
| Careful Selection and Thoughtful Discarding: Graph Explicit Pooling Utilizing Discarded Nodes C Liu, W Yu, K Gao, X Ma, Y Zhan, J Wu, B Du, W Hu arXiv preprint arXiv:2311.12644, 2023 | | 2023 |
| Exploring High-Order Message-Passing in Graph Transformers X Ma, X Ma, C Liu, SM Erfani, J Bailey | | 2023 |
| FEATURE-AUGMENTED HYPERGRAPH NEURAL NETWORKS X Ma, P Li, Q Cao, J Bailey, Y Gao | | 2021 |
| Local Structure Preserving Using Manifold Regularization and Pairwise Constraints for Action Recognition X Ma, Z Cao, W Liu 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW …, 2016 | | 2016 |
| Semi-supervised Hessian Eigenmap for Human Action Recognition X Ma, J Pan, Y Wang, W Liu Intelligent Visual Surveillance: 4th Chinese Conference, IVS 2016, Beijing …, 2016 | | 2016 |
| Graph Explicit Pooling for Graph-Level Representation Learning C Liu, W Yu, K Gao, X Ma, Y Zhan, J Wu, W Hu, B Du Available at SSRN 4774121, 0 | | |
