| Deep fuzzy k-means with adaptive loss and entropy regularization R Zhang, X Li, H Zhang, F Nie IEEE Transactions on Fuzzy Systems 28 (11), 2814-2824, 2019 | 92 | 2019 |
| Embedding graph auto-encoder for graph clustering H Zhang, P Li, R Zhang, X Li IEEE Transactions on Neural Networks and Learning Systems 34 (11), 9352-9362, 2022 | 85* | 2022 |
| Adaptive graph auto-encoder for general data clustering X Li, H Zhang, R Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (12), 9725 …, 2021 | 85 | 2021 |
| Autoencoder constrained clustering with adaptive neighbors X Li, R Zhang, Q Wang, H Zhang IEEE transactions on neural networks and learning systems 32 (1), 443-449, 2020 | 59 | 2020 |
| Robust multi-task learning with flexible manifold constraint R Zhang, H Zhang, X Li IEEE Transactions on Pattern Analysis and Machine Intelligence 43 (6), 2150-2157, 2020 | 33 | 2020 |
| Matrix completion via non-convex relaxation and adaptive correlation learning X Li, H Zhang, R Zhang IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (2), 1981-1991, 2022 | 29 | 2022 |
| Non-Graph Data Clustering via Bipartite Graph Convolution H Zhang, J Shi, R Zhang, X Li IEEE Transactions on Pattern Analysis and Machine Intelligence, 1-13, 2022 | 17 | 2022 |
| Unsupervised feature selection with extended OLSDA via embedding nonnegative manifold structure R Zhang, H Zhang, X Li, S Yang IEEE transactions on neural networks and learning systems 33 (5), 2274-2280, 2020 | 17 | 2020 |
| Maximum joint probability with multiple representations for clustering R Zhang, H Zhang, X Li IEEE transactions on neural networks and learning systems 33 (9), 4300-4310, 2021 | 15 | 2021 |
| Decouple Graph Neural Networks: Train Multiple Simple GNNs Simultaneously Instead of One H Zhang, Y Zhu, X Li IEEE Transactions on Pattern Analysis and Machine Intelligence, 2024 | 8 | 2024 |
| Robust multi-view fuzzy clustering via softmin H Zhang, R Zhang, X Li, Y Xu Neurocomputing 458, 47-55, 2021 | 8 | 2021 |
| Variational Positive-incentive Noise: How Noise Benefits Models H Zhang, S Huang, X Li arXiv preprint arXiv:2306.07651, 2023 | 6 | 2023 |
| Manifold neural network with non-gradient optimization R Zhang, Z Jiao, H Zhang, X Li IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (3), 3986-3993, 2022 | 5 | 2022 |
| Data Augmentation of Contrastive Learning is Estimating Positive-incentive Noise H Zhang, Y Xu, S Huang, X Li arXiv preprint arXiv:2408.09929, 2024 | 4 | 2024 |
| Towards projected clustering with aggregated mapping H Zhang, Y Zhu, X Li IEEE Transactions on Image Processing, 2023 | 3 | 2023 |
| Pivotal-Aware Principal Component Analysis X Li, P Li, H Zhang, K Zhu, R Zhang IEEE Transactions on Neural Networks and Learning Systems, 2023 | 3 | 2023 |
| CNN2GNN: How to Bridge CNN with GNN Z Jiao, H Zhang, X Li arXiv preprint arXiv:2404.14822, 2024 | 1 | 2024 |
| Discretize Relaxed Solution of Spectral Clustering via a Nonheuristic Algorithm H Zhang, X Li IEEE Transactions on Neural Networks and Learning Systems, 2023 | 1 | 2023 |
| Edge Contrastive Learning: An Augmentation-Free Graph Contrastive Learning Model Y Li, H Zhang, Y Yuan arXiv preprint arXiv:2412.11075, 2024 | | 2024 |
| Enhance Vision-Language Alignment with Noise S Huang, H Zhang, X Li arXiv preprint arXiv:2412.10817, 2024 | | 2024 |
Xuelong Li （李学龙）TeleAI, China Telecom （中国电信人工智能研究院 TeleAI）在 ieee.org 的电子邮件经过验证
