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基本信息 The basic information
姓名: 张睿

学院: 光电与智能研究院


学历: 博士研究生毕业

学位: 工学博士


职称: 副教授

职务:


学科: 计算机科学与技术-计算机应用技术


邮箱: ruizhang@nwpu.edu.cn




工作经历 Work Experience
2020- 西北工业大学 副教授
2018-2020 中国科学院西安光学精密机械研究所 博士后





招生信息 Admission Information
招收对机器学习、深度学习和数据挖掘感兴趣的本科和研究生。http://iopen.nwpu.edu.cn/info/1251/1357.htm



学术成果 Academic Achievements
[1] R. Zhang, H. Zhang, and X. Li, "Robust Multi-Task Learning with Flexible Manifold Constraint," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), in press, 2020.
[2]R. Zhang,X. Li, H. Zhang, and Z. Jiao, "GeodesicMulti-Class SVM with Stiefel Manifold Embedding," IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), in press, 2021.
[3] R. Zhang and X. Li, "Regularized Regression with Fuzzy Membership Embedding for Unsupervised Feature Selection," IEEE Transactions on Fuzzy Systems (TFS), in press, 2020.
[4] R. Zhang and X. Li, "Unsupervised Feature Selection Via Data Reconstruction and Side Information," IEEE Transactions on Image Processing (TIP), vol. 29, pp. 8097-8106, 2020.
[5] R. Zhang, X. Li, H. Zhang, and F. Nie, "Deep Fuzzy K-Means with Adaptive Loss and Entropy Regularization," IEEE Transactions on Fuzzy Systems (TFS), vol. 28, no. 11, pp. 2814-2824, 2020.
[6] R. Zhang, F. Nie, and X. Li, "Self-Weighted Supervised Discriminative Feature Selection," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 29, no. 8, pp. 3913-3918, 2018.
[7] R. Zhang, F. Nie, and X. Li, "Semi-Supervised Learning with Parameter-Free Similarity of Label and Side Information," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 2, pp. 405-414, 2019.
[8] R. Zhang, F. Nie, M. Guo, X. Wei, and X. Li, "Joint Learning of Fuzzy K-Means and Nonnegative Spectral Clustering with Side Information," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2152-2162, 2019.
[9] R. Zhang, F. Nie, X. Li, and X. Wei, "Feature Selection with Multi-view Data: A Survey," Information Fusion, vol. 50, pp. 158-167, 2019.
[10] R. Zhang, F. Nie, and X. Li, "Regularized Class-Specific Subspace Classifier," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 28, no. 11, pp. 2738-2747, 2017.
[11] R. Zhang, X. Li, T. Wu, and Y. Zhao, "Data Clustering via Uncorrelated Ridge Regression," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 1, pp. 450-456, 2021.
[12] X. Li, H. Zhang, R. Zhang*, and F. Nie, "Generalized Uncorrelated Regression Model with Adaptive Graph for Unsupervised Feature Selection," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 5, pp. 1587-1595, 2019.
[13] X. Li, R. Zhang*, Q. Wang, and H. Zhang, "Auto-encoder Constrained Clustering with Adaptive Neighbors," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 32, no. 1, pp. 443- 449, 2021.
[14] R. Zhang, H. Zhang, and X. Li, "Maximum Joint Probability With Multiple Representations for Clustering," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2021.
[15] R. Zhang, H. Zhang, X. Li, and F. Nie, "Adaptive Robust Low-rank 2D Reconstruction with Steerable Sparsity," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 9, pp. 3754-3759, 2020.
[16] R. Zhang, F. Nie, Y. Wang, and X. Li, "Unsupervised Feature Selection via Adaptive Multi-Measure Fusion," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 30, no. 9, pp. 2886-2892, 2019.
[17] F. Nie, S. Yang, R. Zhang*, and X. Li, "A General Framework for Auto-weighted Feature Selection via Global Redundancy Minimization," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2428-2438, 2019.
[18] X. Li, Y. Zhang, and R. Zhang*, "Semi-Supervised Feature Selection via Generalized Uncorrelated Constraint and Manifold Embedding," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2020.
[19] T. Wu, R. Zhang*, Z. Jiao, X. Wei, and X. Li, "Adaptive Spectral Rotation via Joint Cluster and Pairwise Structure," IEEE Transactions on Knowledge and Data Engineering (TKDE), in press, 2021.
[20] R. Zhang, Y. Zhang, and X. Li, "Unsupervised Feature Selection via Adaptive Graph Learning and Constraint," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2020.
[21] R. Zhang, H. Zhang, X. Li, and S. Yang, "Unsupervised Feature Selection with Extended OLSDA via Embedding Nonnegative Manifold Structure," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), in press, 2020.
[22] X. Li, H. Zhang, R. Zhang*, and F. Nie, "Discriminative and Uncorrelated Feature Selection with Constrained Spectral Analysis in Unsupervised Learning," IEEE Transactions on Image Processing (TIP), vol. 29, no. 1, pp. 2139-2149, 2020.
[23] Y. Liu, R. Zhang, F. Nie, and X. Li, "Supervised Dimensionality Reduction Methods with Recursive Regression," IEEE Transactions on Neural Networks and Learning Systems (TNNLS), vol. 31, no. 9, pp. 3269-3279, 2020.
[24] F. Nie, H. Zhang, R. Zhang, and X. Li, "Robust multiple rank-k bilinear projections for unsupervised learning," IEEE Transactions on Image Processing (TIP), vol. 28, no. 5, pp. 2574-2583, 2019.
[25] H. Zhang, F. Nie, R. Zhang, and X. Li, "Auto-weighted 2-dimensional Maximum Margin Criterion," Pattern Recognition, vol. 83, pp. 220-229, 2018.
[26] R. Zhang, F. Nie, and X. Li, "Self-Weighted Spectral Clustering with Parameter-Free Constraint," Neurocomputing, vol. 241, pp. 164-170, 2017.
[27] R. Zhang, F. Nie, and X. Li, "Feature Selection under Regularized Orthogonal Least Square Regression with Optimal Scaling," Neurocomputing, vol. 273, pp. 547-553, 2018.
[28] F. Nie, R. Zhang*, and X. Li, "A generalized power iteration method for solving quadratic problem on the Stiefel manifold," Science China Information Sciences, vol. 60, no. 11, pp. 112101, 2017.
[29] T. Wu, Y. Zhou, R. Zhang, Y. Xiao, and F. Nie, "Self-Weighted Discriminative Feature Selection via Adaptive Redundancy Minimization," Neurocomputing, vol. 275, pp. 2824-2830, 2018.
[30] H. Zhang, R. Zhang, F. Nie, and X. Li, "An Efficient Framework for Unsupervised Feature Selection," Neurocomputing, vol. 366, pp. 194-207, 2019.
[31] Y. Zhao, H. Wang, H. Su, L. Zhang, R. Zhang, D. Wang, and K. Xu, "Understand Love of Variety in Wireless Data Market under Sponsored Data Plans," IEEE Journal on Selected Areas in Communications, vol. 38, no. 4, pp. 766-781, 2020.
[32] R. Zhang, F. Nie, and X. Li, "Semi-Supervised Classification via both Label and Side Information," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2417-2421, 2017.
[33] R. Zhang, F. Nie, and X. Li, "Embedded Clustering via Robust Orthogonal Least Square Discriminant Analysis," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2332-2336, 2017.
[34] Y. Zhao, M. Qiao, H. Wang, R. Zhang, D. Wang, K. Xu, and Q. Tan, "TDFI: Two-stage Deep Learning Framework for Friendship Inference via Multi-source Information," IEEE International Conference on Computer Communications (INFOCOM), pp. 1981-1989, 2019.
[35] R. Zhang, F. Nie, and X. Li, "Auto-Weighted Two-Dimensional Principal Component Analysis with Robust Outliers," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 6065-6069, 2017.
[36] H. Zhang, R. Zhang*, F. Nie, and X. Li, "A Generalized Uncorrelated Ridge Regression with Nonnegative Labels for Unsupervised Feature Selection," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2781-2785, 2018.
[37] S. Yang, R. Zhang*, F. Nie, and X. Li, "Unsupervised Feature Selection Based on Reconstruction Error Minimization," IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 2108-2111, 2019.
[38] R. Zhang, H. Tong, Y. Xia, and Y. Zhu, "Robust Embedded Deep K-means Clustering," ACM International Conference on Information and Knowledge Management (CIKM), pp. 1181-1190, 2019.
[39] R. Zhang, H. Tong, and Y. Hu, "Adaptive Feature Redundancy Minimization," ACM International Conference on Information and Knowledge Management (CIKM), pp. 2417-2420, 2019.
[40] M. Guo, R. Zhang, F. Nie, and X. Li, "Embedding Fuzzy K-Means with Nonnegative Spectral Clustering via Incorporating Side Information," ACM International Conference on Information and Knowledge Management (CIKM), pp. 1567-1570, 2018.
[41] R. Zhang and H. Tong, "Robust Principal Component Analysis with Adaptive Neighbors," Thirty-third Conference on Neural Information Processing Systems (NeurIPS), pp. 6959-6967, 2019.





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