Qingyun Wu
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- Advanced Bandit Algorithms Research 13
- Information Systems top 5%
- Recommender Systems and Techniques 6
- Artificial Intelligence top 5%
- Data Stream Mining Techniques 9
- Machine Learning and Data Classification 6
- Machine Learning and Algorithms 5
- Computer Science Applications top 10%
- Mobile Crowdsensing and Crowdsourcing 4
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- Smart Grid Energy Management 3
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- Advanced Multi-Objective Optimization Algorithms 2
- Journals
- Journal of Membrane Science (1 paper)Mathematics of Operations Research (1 paper)Games and Economic Behavior (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Qingyun Wu
28 papers receiving 503 citations
Peers
Comparison fields: 5 of 77
- Management Science and Operations Research 229
- Information Systems 254
- Artificial Intelligence 300
- Computer Science Applications 28
- Computer Vision and Pattern Recognition 46
Countries citing papers authored by Qingyun Wu
This map shows the geographic impact of Qingyun Wu'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 Qingyun Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qingyun Wu more than expected).
Fields of papers citing papers by Qingyun Wu
This network shows the impact of papers produced by Qingyun Wu. 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 Qingyun Wu. The network helps show where Qingyun Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Qingyun Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 16 | |
| 3 | 2024 | 4 | |
| 4 | 2023 | 14 | |
| 5 | 2022 | 1 | |
| 6 | ECONOMIC HYPERPARAMETER OPTIMIZATION WITH BLENDED SEARCH STRATEGY | 2021 | 5 |
| 7 | FLAML: A Fast and Lightweight AutoML Library | 2021 | 51 |
| 8 | 2021 | 16 | |
| 9 | 2020 | 18 | |
| 10 | FLO: Fast and Lightweight Hyperparameter Optimization for AutoML. | 2019 | 4 |
| 11 | 2019 | 14 | |
| 12 | 2018 | 18 | |
| 13 | Bandit Learning with Implicit Feedback | 2018 | 9 |
| 14 | 2017 | 39 | |
| 15 | 2016 | 55 | |
| 16 | The anlysis and estimation of the mineral resources situation in China since new century | 2011 | 1 |
| 17 | A dream of glory : fanhua meng : a Chinese play by Wang Yun | 2008 | 2 |
| 18 | 2007 | 2 | |
| 19 | Adaptive robust control with L_2-gain for a class of uncertain nonlinear systems | 2006 | 2 |
| 20 | Adaptive Sliding Mode Control for the Global Trajectory Tracking of Mobile Robots | 2006 | 2 |
About Qingyun Wu
Qingyun Wu is a scholar working on Management Science and Operations Research, Computer Science Applications and Artificial Intelligence, having authored 30 papers that have together received 518 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (13 papers), Data Stream Mining Techniques (9 papers), Machine Learning and Data Classification (6 papers), Recommender Systems and Techniques (6 papers), Machine Learning and Algorithms (5 papers), Mobile Crowdsensing and Crowdsourcing (4 papers), Smart Grid Energy Management (3 papers) and Advanced Multi-Objective Optimization Algorithms (2 papers). The work is most often cited by research in Management Science and Operations Research (229 citations), Information Systems (254 citations) and Artificial Intelligence (300 citations). Qingyun Wu has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include Hongning Wang, Huazheng Wang, Chi Wang, Quanquan Gu, Erkang Zhu, Markus Weimer, Xiangnan He, Shijun Li, Tat‐Seng Chua and Wenqiang Lei. Their work appears in journals such as Journal of Membrane Science, Mathematics of Operations Research and Games and Economic Behavior.
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.