张佳

发布者:2023-11-17发布者:125

[1] J. Zhang, H. Wu, M. Jiang, J. Liu, S. Li, Y. Tang, J. Long. Group-preserving label-specific feature selection for multi-label learning. Expert Systems with Applications, 2023, 213: 118861.

[2] J. Zhang, Y. Lin, M. Jiang, S. Li, Y. Tang, J. Long, J. Weng, K. C. Tan. Fast multi-label feature selection via global relevance and redundancy optimization. IEEE Transactions on Neural Networks and Learning Systems (Early Access), 2022.

[3] D. Liu, J. Zhang, H. Wu, S. Liu, J. Long. Multi-source transfer learning for EEG classification based on domain adversarial neural network. IEEE Transactions on Neural Systems and Rehabilitation Engineering (Early Access), 2022.

[4] S. Liu, J. Zhang, A. Wang, H. Wu, Q. Zhao, J. Long. Subject adaptation convolutional neural network for EEG-based motor imagery classification. Journal of Neural Engineering, IOP Publishing, 2022.

[5] A. Tan, J. Liang, W.-Z. Wu, J. Zhang. Semi-supervised partial multi-label classification via consistency learning. Pattern Recognition, Elsevier BV, 2022, 131: 108839.

[6] J. Zhang, S. Li, M. Jiang, K. C. Tan. Learning from weakly labeled data based on manifold regularized sparse model. IEEE Transactions on Cybernetics, 2022, 52(5): 3841-3854.

[7] G. Du, J. Zhang, M. Jiang, J. Long, Y. Lin, S. Li, K. C. Tan. Graph-based class-imbalance learning with label enhancement. IEEE Transactions on Neural Networks and Learning Systems (Early Access), 2021.

[8] Z.-A. Huang, J. Zhang, Z. Zhu, E. Q. Wu, K. C. Tan. Identification of autistic risk candidate genes and toxic chemicals via multi-label learning. IEEE Transactions on Neural Networks and Learning Systems, 2021, 32(9): 3971-3984.

[9] J. Zhang, Y. Lin, M. Jiang, S. Li, Y. Tang, K. C. Tan. Multi-label feature selection via global relevance and redundancy optimization. In Proceedings of the 29th International Joint Conference on Artificial Intelligence, Yokohama, Japan, 2020, pp. 2512–2518.

[10] J. Zhang, Z. Luo, C. Li, C. Zhou, S. Li. Manifold regularized discriminative feature selection for multi-label learning. Pattern Recognition, 2019, 95: 136-150.