Wenkui Ding
Impact in
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Video Analysis and Summarization
- Human Pose and Action Recognition
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- Advanced Bandit Algorithms Research
Papers in
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- Machine Learning and Algorithms 2
- Domain Adaptation and Few-Shot Learning 1
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- Optimization and Search Problems 3
- Co-authors
- Xudong Zhang (2 shared papers)Shengsheng Qian (2 shared papers)Tie‐Yan Liu (3 shared papers)Xiubo Geng (1 shared paper)Tao Qin (3 shared papers)Song Liu (1 shared paper)Haoqi Fan (1 shared paper)Yiru Chen (1 shared paper)
- Journals
- Neurocomputing (1 paper)IEEE Transactions on Multimedia (1 paper)ACM Transactions on Intelligent Systems and Technology (1 paper)Agricultural Water Management (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Wenkui Ding
9 papers receiving 364 citations
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 160
- Management Science and Operations Research 91
- Artificial Intelligence 151
- Information Systems 87
- Computer Science Applications 19
Countries citing papers authored by Wenkui Ding
This map shows the geographic impact of Wenkui Ding'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 Wenkui Ding with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenkui Ding more than expected).
Fields of papers citing papers by Wenkui Ding
This network shows the impact of papers produced by Wenkui Ding. 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 Wenkui Ding. The network helps show where Wenkui Ding may publish in the future.
Co-authors
The 25 scholars most cited alongside Wenkui Ding, 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 | 2021 | 111 | |
| 2 | 2013 | 73 | |
| 3 | 2015 | 71 | |
| 4 | 2022 | 42 | |
| 5 | 2012 | 30 | |
| 6 | A neural autoregressive approach to collaborative filtering | 2016 | 23 |
| 7 | 2017 | 11 | |
| 8 | Budgeted Bandit Problems with Continuous Random Costs | 2015 | 9 |
| 9 | 2023 | 6 |
About Wenkui Ding
Wenkui Ding is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Management Science and Operations Research and Computer Vision and Pattern Recognition, having authored 9 papers that have together received 376 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (3 papers), Optimization and Search Problems (3 papers), Advanced Bandit Algorithms Research (3 papers), Information Retrieval and Search Behavior (2 papers), Machine Learning and Algorithms (2 papers), Domain Adaptation and Few-Shot Learning (1 paper), Consumer Market Behavior and Pricing (1 paper) and Plant Water Relations and Carbon Dynamics (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (160 citations), Management Science and Operations Research (91 citations), Artificial Intelligence (151 citations), Information Systems (87 citations) and Computer Science Applications (19 citations). Wenkui Ding has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Xudong Zhang, Shengsheng Qian, Tie‐Yan Liu, Xiubo Geng, Tao Qin, Song Liu, Haoqi Fan, Yiru Chen, Zhongyuan Wang and Changsheng Xu. Their work appears in journals such as Neurocomputing, IEEE Transactions on Multimedia, ACM Transactions on Intelligent Systems and Technology, Agricultural Water Management and Proceedings of the AAAI Conference on Artificial Intelligence.
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.