Gengyu Lyu

585 total citations
30 papers, 395 citations indexed

About

Gengyu Lyu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems. According to data from OpenAlex, Gengyu Lyu has authored 30 papers receiving a total of 395 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 16 papers in Computer Vision and Pattern Recognition and 8 papers in Information Systems. Recurrent topics in Gengyu Lyu's work include Text and Document Classification Technologies (20 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Web Data Mining and Analysis (6 papers). Gengyu Lyu is often cited by papers focused on Text and Document Classification Technologies (20 papers), Advanced Image and Video Retrieval Techniques (7 papers) and Web Data Mining and Analysis (6 papers). Gengyu Lyu collaborates with scholars based in China, Canada and Singapore. Gengyu Lyu's co-authors include Songhe Feng, Yidong Li, Congyan Lang, Tao Wang, Lijuan Sun, Guojun Dai, Jun Liu, Yi Jin, Jiazheng Yuan and Hua Zhang and has published in prestigious journals such as IEEE Transactions on Signal Processing, Information Sciences and IEEE Transactions on Cybernetics.

In The Last Decade

Gengyu Lyu

25 papers receiving 390 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gengyu Lyu China	12	359	239	101	56	21	30	395
Ming-Kun Xie China	8	279 0.8×	136 0.6×	86 0.9×	50 0.9×	17 0.8×	16	303
Juncheng Hu China	8	254 0.7×	201 0.8×	60 0.6×	52 0.9×	30 1.4×	22	293
Siddharth Gopal United States	9	240 0.7×	105 0.4×	76 0.8×	25 0.4×	6 0.3×	11	303
Sabri Boutemedjet Canada	8	188 0.5×	197 0.8×	55 0.5×	15 0.3×	7 0.3×	12	315
Binyuan Hui China	9	214 0.6×	90 0.4×	56 0.6×	11 0.2×	6 0.3×	22	271
Julie Borsack United States	11	226 0.6×	177 0.7×	123 1.2×	14 0.3×	20 1.0×	22	332
Allen Condit United States	9	193 0.5×	144 0.6×	106 1.0×	13 0.2×	16 0.8×	19	279
Lazhar Labiod France	8	165 0.5×	84 0.4×	25 0.2×	15 0.3×	10 0.5×	25	218
Hwee-Boon Low Singapore	4	244 0.7×	65 0.3×	122 1.2×	18 0.3×	8 0.4×	7	285
Yi Wen China	6	187 0.5×	162 0.7×	22 0.2×	7 0.1×	6 0.3×	8	257

Countries citing papers authored by Gengyu Lyu

Since Specialization

Citations

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

Fields of papers citing papers by Gengyu Lyu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gengyu Lyu

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

All Works

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20 of 20 papers shown

Zhu, G., et al.. (2025). Large Margin Representation Learning for Robust Cross-lingual Named Entity Recognition. 4270–4291.

Hao, Wei, et al.. (2025). Multi-View Multi-Label Classification via View-Label Matching Selection. Proceedings of the AAAI Conference on Artificial Intelligence. 39(20). 21456–21464.

Deng, Yongjian, et al.. (2025). CFDM: Contrastive Fusion and Disambiguation for Multi-View Partial-Label Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 39(16). 17005–17013.

Wang, Jing, Songhe Feng, Gengyu Lyu, & Jiazheng Yuan. (2024). SURER: Structure-Adaptive Unified Graph Neural Network for Multi-View Clustering. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 15520–15527. 8 indexed citations

Xia, Mingxuan, Junbo Zhao, Gengyu Lyu, et al.. (2024). A Separation and Alignment Framework for Black-Box Domain Adaptation. Proceedings of the AAAI Conference on Artificial Intelligence. 38(14). 16005–16013. 1 indexed citations

Feng, Songhe, et al.. (2023). MetaZSCIL: A Meta-Learning Approach for Generalized Zero-Shot Class Incremental Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(9). 10408–10416. 6 indexed citations

Wang, Haobo, Gengyu Lyu, Weiwei Liu, et al.. (2023). Deep Partial Multi-Label Learning with Graph Disambiguation. 4308–4316. 4 indexed citations

Feng, Songhe, et al.. (2023). Triple-Granularity Contrastive Learning for Deep Multi-View Subspace Clustering. 2994–3002. 15 indexed citations

Feng, Songhe, et al.. (2022). Beyond Word Embeddings: Heterogeneous Prior Knowledge Driven Multi-Label Image Classification. IEEE Transactions on Multimedia. 25. 4013–4025. 14 indexed citations

10.

Feng, Songhe, et al.. (2022). Distance-Preserving Embedding Adaptive Bipartite Graph Multi-View Learning with Application to Multi-Label Classification. ACM Transactions on Knowledge Discovery from Data. 17(2). 1–21. 5 indexed citations

11.

Wang, Shaokai, et al.. (2022). Partial label learning with noisy side information. Applied Intelligence. 52(11). 12382–12396. 3 indexed citations

12.

Lyu, Gengyu, et al.. (2022). Deep Graph Matching for Partial Label Learning. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 3306–3312. 7 indexed citations

13.

Lang, Congyan, et al.. (2021). Class-Balanced Text to Image Synthesis With Attentive Generative Adversarial Network. IEEE Multimedia. 28(3). 21–31. 3 indexed citations

14.

Lyu, Gengyu, Songhe Feng, & Yidong Li. (2020). Partial Multi-Label Learning via Probabilistic Graph Matching Mechanism. 105–113. 34 indexed citations

15.

Lyu, Gengyu, Songhe Feng, Yidong Li, et al.. (2020). HERA. ACM Transactions on Intelligent Systems and Technology. 11(3). 1–19. 14 indexed citations

16.

Lyu, Gengyu, Songhe Feng, & Yidong Li. (2020). Noisy label tolerance: A new perspective of Partial Multi-Label Learning. Information Sciences. 543. 454–466. 42 indexed citations

17.

Sun, Lijuan, Songhe Feng, Gengyu Lyu, Hua Zhang, & Guojun Dai. (2020). Partial multi-label learning with noisy side information. Knowledge and Information Systems. 63(2). 541–564. 17 indexed citations

18.

Lyu, Gengyu, et al.. (2020). Partial Multi-Label Learning via Multi-Subspace Representation. 2612–2618. 34 indexed citations

19.

Lang, Congyan, et al.. (2020). Attentive Generative Adversarial Network To Bridge Multi-Domain Gap For Image Synthesis. 1–6. 10 indexed citations

20.

Lyu, Gengyu, et al.. (2019). Partial label learning via low-rank representation and label propagation. Soft Computing. 24(7). 5165–5176. 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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