Lele Fu

722 total citations · 1 hit paper
27 papers, 464 citations indexed

About

Lele Fu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mathematics. According to data from OpenAlex, Lele Fu has authored 27 papers receiving a total of 464 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Artificial Intelligence, 17 papers in Computer Vision and Pattern Recognition and 8 papers in Computational Mathematics. Recurrent topics in Lele Fu's work include Face and Expression Recognition (11 papers), Tensor decomposition and applications (8 papers) and Video Surveillance and Tracking Methods (7 papers). Lele Fu is often cited by papers focused on Face and Expression Recognition (11 papers), Tensor decomposition and applications (8 papers) and Video Surveillance and Tracking Methods (7 papers). Lele Fu collaborates with scholars based in China, Hong Kong and Macao. Lele Fu's co-authors include Shiping Wang, Athanasios V. Vasilakos, Pengfei Lin, Zhaoliang Chen, Chuan Chen, Claudia Plant, Wenzhong Guo, Jing‐Hua Yang, Chuanfu Zhang and Zibin Zheng and has published in prestigious journals such as Information Sciences, IEEE Transactions on Neural Networks and Learning Systems and Neurocomputing.

In The Last Decade

Lele Fu

24 papers receiving 461 citations

Hit Papers

Learnable graph convolutional network and feature fusion ... 2023 2026 2024 2025 2023 25 50 75 100
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Learnable graph convolutional network and feature fusion for multi-view learning
    2023 110 citations Zhaoliang Chen, Lele Fu et al. Information Fusion profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lele Fu China 10 290 271 52 46 45 27 464
Danyang Wu China 14 404 1.4× 365 1.3× 83 1.6× 22 0.5× 88 2.0× 43 607
Xinzhong Zhu China 5 455 1.6× 377 1.4× 69 1.3× 25 0.5× 124 2.8× 15 641
Chong Peng United States 10 315 1.1× 210 0.8× 25 0.5× 20 0.4× 101 2.2× 17 461
Lai Tian China 10 346 1.2× 249 0.9× 59 1.1× 12 0.3× 86 1.9× 14 469
Shide Du China 11 219 0.8× 231 0.9× 42 0.8× 9 0.2× 33 0.7× 28 345
Bassoma Diallo China 8 196 0.7× 168 0.6× 30 0.6× 9 0.2× 35 0.8× 12 300
Gui‐Fu Lu China 11 300 1.0× 105 0.4× 24 0.5× 26 0.6× 71 1.6× 37 372
Gui-Fu Lu China 12 341 1.2× 127 0.5× 24 0.5× 39 0.8× 84 1.9× 35 412
Kewei Tang China 9 236 0.8× 90 0.3× 25 0.5× 14 0.3× 86 1.9× 26 311

Countries citing papers authored by Lele Fu

Since Specialization
Citations

This map shows the geographic impact of Lele Fu's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lele Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lele Fu more than expected).

Fields of papers citing papers by Lele Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lele Fu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lele Fu. The network helps show where Lele Fu may publish in the future.

Co-authorship network of co-authors of Lele Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Lele Fu. A scholar is included among the top collaborators of Lele Fu based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lele Fu. Lele Fu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Fu, Lele, Lei Yang, Chuan Chen, et al.. (2025). Privacy-Preserving Vertical Federated Learning With Tensor Decomposition for Data Missing Features. IEEE Transactions on Information Forensics and Security. 20. 3445–3460.
2.
Fu, Lele, et al.. (2025). Learn the global prompt in the low-rank tensor space for heterogeneous federated learning. Neural Networks. 187. 107319–107319.
3.
Fu, Lele, et al.. (2025). Parameter-oriented contrastive schema and multi-level knowledge distillation for heterogeneous federated learning. Information Fusion. 121. 103123–103123. 2 indexed citations
4.
Fu, Lele, et al.. (2025). Federated Domain-Independent Prototype Learning With Alignments of Representation and Parameter Spaces for Feature Shift. IEEE Transactions on Mobile Computing. 24(9). 9004–9019.
5.
Fu, Lele, et al.. (2024). A Cross-Client Coordinator in Federated Learning Framework for Conquering Heterogeneity. IEEE Transactions on Neural Networks and Learning Systems. 36(5). 8828–8842. 3 indexed citations
6.
Fu, Lele, et al.. (2024). Toward Few-Label Vertical Federated Learning. ACM Transactions on Knowledge Discovery from Data. 18(7). 1–21. 5 indexed citations
7.
Fu, Lele, et al.. (2024). Hyper-Laplacian Regularized Concept Factorization in Low-Rank Tensor Space for Multi-View Clustering. IEEE Transactions on Emerging Topics in Computational Intelligence. 9(2). 1728–1742. 1 indexed citations
8.
Du, Shide, et al.. (2024). Tensor-Derived Large-Scale Multi-View Subspace Clustering With Faithful Semantics. IEEE Transactions on Signal and Information Processing over Networks. 10. 584–598. 2 indexed citations
9.
Fu, Lele, et al.. (2024). Subspace-Contrastive Multi-View Clustering. ACM Transactions on Knowledge Discovery from Data. 18(9). 1–35. 6 indexed citations
10.
Fu, Lele, et al.. (2024). Data-free knowledge distillation via generator-free data generation for Non-IID federated learning. Neural Networks. 179. 106627–106627. 7 indexed citations
11.
Fu, Lele, et al.. (2023). Mutual Information-Driven Multi-View Clustering. 3268–3277. 9 indexed citations
12.
Chen, Zhaoliang, et al.. (2023). Learnable graph convolutional network and feature fusion for multi-view learning. Information Fusion. 95. 109–119. 110 indexed citations breakdown →
13.
Chen, Zhaoliang, Lele Fu, Shunxin Xiao, et al.. (2023). Multi-View Graph Convolutional Networks with Differentiable Node Selection. ACM Transactions on Knowledge Discovery from Data. 18(1). 1–21. 9 indexed citations
14.
Fu, Lele, Zhaoliang Chen, Yongyong Chen, & Shiping Wang. (2022). Unified Low-Rank Tensor Learning and Spectral Embedding for Multi-View Subspace Clustering. IEEE Transactions on Multimedia. 25. 4972–4985. 40 indexed citations
15.
Fu, Lele, Jieling Li, & Chuan Chen. (2022). Consistent affinity representation learning with dual low-rank constraints for multi-view subspace clustering. Neurocomputing. 514. 113–126. 7 indexed citations
16.
Fu, Lele, et al.. (2022). Learnable Multi-View Matrix Factorization With Graph Embedding and Flexible Loss. IEEE Transactions on Multimedia. 25. 3259–3272. 20 indexed citations
17.
Yang, Jing‐Hua, Chuan Chen, Hong‐Ning Dai, Lele Fu, & Zibin Zheng. (2022). A structure noise-aware tensor dictionary learning method for high-dimensional data clustering. Information Sciences. 612. 87–106. 9 indexed citations
18.
Yang, Jing‐Hua, Chuan Chen, Hong‐Ning Dai, et al.. (2022). Hierarchical Representation for Multi-view Clustering. Proceedings of the 31st ACM International Conference on Information & Knowledge Management. 2362–2371. 3 indexed citations
19.
Fu, Lele, et al.. (2021). Multi-View Learning Via Low-Rank Tensor Optimization. 1–6. 12 indexed citations
20.
Fu, Lele, Pengfei Lin, Athanasios V. Vasilakos, & Shiping Wang. (2020). An overview of recent multi-view clustering. Neurocomputing. 402. 148–161. 132 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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