Wei-Wei Tu

1.3k total citations
34 papers, 383 citations indexed

About

Wei-Wei Tu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics. According to data from OpenAlex, Wei-Wei Tu has authored 34 papers receiving a total of 383 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 5 papers in Computational Theory and Mathematics. Recurrent topics in Wei-Wei Tu's work include Machine Learning and Data Classification (9 papers), Machine Learning and Algorithms (4 papers) and Topic Modeling (4 papers). Wei-Wei Tu is often cited by papers focused on Machine Learning and Data Classification (9 papers), Machine Learning and Algorithms (4 papers) and Topic Modeling (4 papers). Wei-Wei Tu collaborates with scholars based in China, United States and Hong Kong. Wei-Wei Tu's co-authors include Quanming Yao, Huan Zhao, R. W. Mayne, Zhanxing Zhu, Yu-Feng Li, Ju Xu, Qiang Yang, Wenyuan Dai, Yuqiang Chen and Hao Zhou and has published in prestigious journals such as Genome biology, International Journal for Numerical Methods in Engineering and Machine Learning.

In The Last Decade

Wei-Wei Tu

30 papers receiving 369 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wei-Wei Tu China 12 255 113 71 36 26 34 383
Qingqing Long China 9 216 0.8× 89 0.8× 51 0.7× 18 0.5× 14 0.5× 19 329
Zhongmin Yan China 11 212 0.8× 70 0.6× 117 1.6× 25 0.7× 25 1.0× 78 354
Bingbing Xu China 8 197 0.8× 65 0.6× 49 0.7× 10 0.3× 19 0.7× 18 303
Longfei Li China 9 323 1.3× 70 0.6× 99 1.4× 15 0.4× 11 0.4× 28 432
Péricles Miranda Brazil 13 295 1.2× 56 0.5× 62 0.9× 88 2.4× 19 0.7× 70 504
Eghbal G. Mansoori Iran 12 356 1.4× 120 1.1× 74 1.0× 104 2.9× 41 1.6× 50 571
Yuhang Jiao China 6 151 0.6× 76 0.7× 69 1.0× 19 0.5× 9 0.3× 14 287
Chengwei Yao China 12 311 1.2× 153 1.4× 95 1.3× 10 0.3× 14 0.5× 19 428

Countries citing papers authored by Wei-Wei Tu

Since Specialization
Citations

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

Fields of papers citing papers by Wei-Wei Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Wei-Wei Tu. 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 Wei-Wei Tu. The network helps show where Wei-Wei Tu may publish in the future.

Co-authorship network of co-authors of Wei-Wei Tu

This figure shows the co-authorship network connecting the top 25 collaborators of Wei-Wei Tu. A scholar is included among the top collaborators of Wei-Wei Tu 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 Wei-Wei Tu. Wei-Wei Tu 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.
Tu, Wei-Wei, et al.. (2025). Optimal large-scale stochastic optimization of NDCG surrogates for deep learning. Machine Learning. 114(2).
2.
Huang, Shi‐Yu, et al.. (2024). DGPO: Discovering Multiple Strategies with Diversity-Guided Policy Optimization. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11390–11398.
3.
Chen, Junzhe, et al.. (2024). LLMArena: Assessing Capabilities of Large Language Models in Dynamic Multi-Agent Environments. 13055–13077. 3 indexed citations
4.
Tu, Wei-Wei, et al.. (2024). Safe Abductive Learning in the Presence of Inaccurate Rules. Proceedings of the AAAI Conference on Artificial Intelligence. 38(15). 16361–16369.
5.
Huang, Shi‐Yu, et al.. (2024). MQE: Unleashing the Power of Interaction with Multi-agent Quadruped Environment. 5918–5924. 1 indexed citations
6.
Sun, Yu, Xiang Xu, Lin Lin, et al.. (2023). A graph neural network-based interpretable framework reveals a novel DNA fragility–associated chromatin structural unit. Genome biology. 24(1). 90–90. 11 indexed citations
7.
Xu, Zhen, Sérgio Escalera, Magali Richard, et al.. (2022). Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform. Patterns. 3(7). 100543–100543. 12 indexed citations
8.
Tu, Wei-Wei, et al.. (2022). Strongly adaptive online learning over partial intervals. Science China Information Sciences. 65(10). 1 indexed citations
9.
Tu, Wei-Wei, et al.. (2022). Transfer and share: semi-supervised learning from long-tailed data. Machine Learning. 113(4). 1725–1742. 8 indexed citations
10.
Tu, Wei-Wei, et al.. (2022). Online strongly convex optimization with unknown delays. Machine Learning. 111(3). 871–893. 4 indexed citations
11.
Tu, Wei-Wei, et al.. (2022). LTU Attacker for Membership Inference. Algorithms. 15(7). 254–254. 1 indexed citations
12.
Gao, Jun, et al.. (2022). Translation-Based Implicit Annotation Projection for Zero-Shot Cross-Lingual Event Argument Extraction. Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval. 2076–2081. 10 indexed citations
13.
Zhao, Huan, Quanming Yao, & Wei-Wei Tu. (2021). Search to aggregate neighborhood for graph neural network. 552–563. 53 indexed citations
14.
Tu, Wei-Wei, et al.. (2021). Towards Robust Prediction on Tail Labels. 1812–1820. 9 indexed citations
15.
Wang, Jingsong, et al.. (2021). Auto-KWS 2021 Challenge: Task, Datasets, and Baselines. 4244–4248. 3 indexed citations
16.
Tu, Wei-Wei, et al.. (2020). Projection-free Distributed Online Convex Optimization with $O(\sqrt{T})$ Communication Complexity. International Conference on Machine Learning. 1. 9818–9828. 5 indexed citations
17.
Yao, Quanming, Ju Xu, Wei-Wei Tu, & Zhanxing Zhu. (2020). Efficient Neural Architecture Search via Proximal Iterations. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 6664–6671. 57 indexed citations
18.
Yao, Quanming, Ju Xu, Wei-Wei Tu, & Zhanxing Zhu. (2019). Differentiable Neural Architecture Search via Proximal Iterations.. arXiv (Cornell University). 3 indexed citations
19.
Yao, Quanming, et al.. (2018). Privacy-preserving Transfer Learning for Knowledge Sharing.. arXiv (Cornell University). 3 indexed citations
20.
Zheng, Wei, Lindan Ji, Wenhua Xing, Wei-Wei Tu, & Jin Xu. (2013). Advances in genome-wide association study of tuberculosis. Hereditas (Beijing). 35(7). 823–829. 1 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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