Lingfeng Niu

1.8k total citations · 1 hit paper
82 papers, 1.2k citations indexed

About

Lingfeng Niu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Mechanics. According to data from OpenAlex, Lingfeng Niu has authored 82 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 62 papers in Artificial Intelligence, 45 papers in Computer Vision and Pattern Recognition and 20 papers in Computational Mechanics. Recurrent topics in Lingfeng Niu's work include Face and Expression Recognition (25 papers), Sparse and Compressive Sensing Techniques (20 papers) and Advanced Graph Neural Networks (17 papers). Lingfeng Niu is often cited by papers focused on Face and Expression Recognition (25 papers), Sparse and Compressive Sensing Techniques (20 papers) and Advanced Graph Neural Networks (17 papers). Lingfeng Niu collaborates with scholars based in China, United States and Australia. Lingfeng Niu's co-authors include Jianyu Miao, Yong Shi, Yingjie Tian, Zhiquan Qi, Minglong Lei, Pei Quan, Xin Shen, Rongrong Ma, Ya-xiang Yuan and Xiaojun Chen and has published in prestigious journals such as Expert Systems with Applications, IEEE Access and Pattern Recognition.

In The Last Decade

Lingfeng Niu

75 papers receiving 1.2k citations

Hit Papers

align trajectories

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.

A Survey on Feature Selection

2016 342 citations Jianyu Miao, Lingfeng Niu Procedia Computer Science profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Lingfeng Niu China	16	711	447	155	104	75	82	1.2k
Julio López Chile	17	708 1.0×	351 0.8×	96 0.6×	74 0.7×	101 1.3×	54	1.2k
Han Liu China	20	495 0.7×	308 0.7×	161 1.0×	64 0.6×	83 1.1×	71	1.2k
Piyush Rai India	19	1.1k 1.6×	917 2.1×	139 0.9×	107 1.0×	97 1.3×	102	2.0k
Hangjun Che China	23	585 0.8×	509 1.1×	177 1.1×	36 0.3×	75 1.0×	73	1.3k
Huan Zhang China	15	882 1.2×	213 0.5×	67 0.4×	93 0.9×	105 1.4×	65	1.3k
Ayhan Demiriz Türkiye	11	888 1.2×	550 1.2×	79 0.5×	63 0.6×	168 2.2×	30	1.4k
Bin Gu China	8	414 0.6×	330 0.7×	56 0.4×	47 0.5×	89 1.2×	10	1000
Deli Zhao China	18	798 1.1×	708 1.6×	42 0.3×	110 1.1×	126 1.7×	57	1.5k
Reshma Rastogi India	21	734 1.0×	706 1.6×	90 0.6×	67 0.6×	70 0.9×	67	1.3k

Countries citing papers authored by Lingfeng Niu

Since Specialization

Citations

This map shows the geographic impact of Lingfeng Niu'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 Lingfeng Niu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lingfeng Niu more than expected).

Fields of papers citing papers by Lingfeng Niu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lingfeng Niu. 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 Lingfeng Niu. The network helps show where Lingfeng Niu may publish in the future.

Co-authorship network of co-authors of Lingfeng Niu

This figure shows the co-authorship network connecting the top 25 collaborators of Lingfeng Niu. A scholar is included among the top collaborators of Lingfeng Niu 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 Lingfeng Niu. Lingfeng Niu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Shi, Yong, et al.. (2024). A universal network strategy for lightspeed computation of entropy-regularized optimal transport. Neural Networks. 184. 107038–107038.

2.

Niu, Lingfeng, et al.. (2024). A Brief Survey on Graph Anomaly Detection. Procedia Computer Science. 242. 1263–1270.

3.

Quan, Pei, et al.. (2024). A Brief Survey of Distribution Robust Graph Neural Networks. Procedia Computer Science. 242. 1281–1286.

4.

Wang, Shengchao, et al.. (2024). Enhancing cut selection through reinforcement learning. Science China Mathematics. 67(6). 1377–1394.

5.

Shi, Yong, et al.. (2024). Wasserstein distance regularized graph neural networks. Information Sciences. 670. 120608–120608. 5 indexed citations

6.

Quan, Pei, et al.. (2024). ExGAT: Context extended graph attention neural network. Neural Networks. 181. 106784–106784. 3 indexed citations

7.

Niu, Lingfeng, et al.. (2023). Two-level adversarial attacks for graph neural networks. Information Sciences. 654. 119877–119877. 2 indexed citations

8.

Shi, Yong, Yuanying Zhang, Peng Zhang, Yang Xiao, & Lingfeng Niu. (2023). Federated learning with ℓ1 regularization. Pattern Recognition Letters. 172. 15–21. 9 indexed citations

9.

Shi, Yong, et al.. (2022). A lightweight network for COVID-19 detection in X-ray images. Methods. 209. 29–37. 1 indexed citations

10.

Xiao, Yang, Pei Quan, Minglong Lei, & Lingfeng Niu. (2022). Latent neighborhood-based heterogeneous graph representation. Neural Networks. 154. 413–424. 7 indexed citations

11.

Shi, Yong, Pei Quan, Tianlin Zhang, & Lingfeng Niu. (2022). DREAM: Drug-drug interaction extraction with enhanced dependency graph and attention mechanism. Methods. 203. 152–159. 16 indexed citations

12.

Quan, Pei, et al.. (2022). Optimal Transport Guided Node Classification in Cross Networks. Procedia Computer Science. 214. 1160–1167. 1 indexed citations

13.

Niu, Lingfeng, et al.. (2020). Unsupervised feature selection for attributed graphs. Expert Systems with Applications. 168. 114402–114402. 6 indexed citations

14.

Ma, Rongrong, et al.. (2019). Transformedℓ1regularization for learning sparse deep neural networks. Neural Networks. 119. 286–298. 74 indexed citations

15.

Shi, Yong, et al.. (2018). Evaluating Doctor Performance: Ordinal Regression-Based Approach. Journal of Medical Internet Research. 20(7). e240–e240. 7 indexed citations

16.

Shi, Yong, Jianyu Miao, & Lingfeng Niu. (2018). Feature selection with MCP $$^2$$ 2 regularization. Neural Computing and Applications. 31(10). 6699–6709. 5 indexed citations

17.

Ma, Rongrong & Lingfeng Niu. (2018). A Survey of Sparse-Learning Methods for Deep Neural Networks. 5. 647–650. 5 indexed citations

18.

Shi, Yong, et al.. (2018). Feature Selection With <inline-formula> <tex-math notation="LaTeX">$\ell_{2,1-2}$ </tex-math> </inline-formula> Regularization. IEEE Transactions on Neural Networks and Learning Systems. 29(10). 4967–4982. 60 indexed citations

19.

Niu, Lingfeng, Yong Shi, & Jianmin Wu. (2012). Learning Using Privileged Information with L-1 Support Vector Machine.. 10–14. 1 indexed citations

20.

Niu, Lingfeng & Jianmin Wu. (2012). Nonlinear L-1 Support Vector Machines for Learning Using Privileged Information. 5. 495–499. 10 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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