Hui Qian
- Artificial Intelligence top 10%
- Statistical and Nonlinear Physics top 5%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Electrical and Electronic Engineering
- Topics
- Stochastic Gradient Optimization Techniques (7 papers)Sparse and Compressive Sensing Techniques (4 papers)Neural Networks and Applications (3 papers)
- Cited by
- Statistical and Nonlinear PhysicsComputational MathematicsComputer Vision and Pattern Recognition
- Partner nations
- ChinaUnited StatesSwitzerland
In The Last Decade
Hui Qian
25 papers receiving 361 citations
Peers
Comparison fields: 5 of 87
- Artificial Intelligence 121
- Statistical and Nonlinear Physics 111
- Computer Vision and Pattern Recognition 104
- Computer Networks and Communications 72
- Electrical and Electronic Engineering 55
Countries citing papers authored by Hui Qian
This map shows the geographic impact of Hui Qian'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 Hui Qian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hui Qian more than expected).
Fields of papers citing papers by Hui Qian
This network shows the impact of papers produced by Hui Qian. 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 Hui Qian. The network helps show where Hui Qian may publish in the future.
Co-authorship network of co-authors of Hui Qian
This figure shows the co-authorship network connecting the top 25 collaborators of Hui Qian. A scholar is included among the top collaborators of Hui Qian 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 Hui Qian. Hui Qian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 11 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | Decentralized Gradient Tracking for Continuous DR-Submodular Maximization | 3 |
| 9 | Hessian Aided Policy Gradient | 11 |
| 10 | 35 | |
| 11 | 22 | |
| 12 | 24 | |
| 13 | 103 | |
| 14 | 4 | |
| 15 | Adaptive variance reducing for stochastic gradient descent | 9 |
| 16 | Making Fisher Discriminant Analysis Scalable | 7 |
| 17 | 4 | |
| 18 | 45 | |
| 19 | 5 | |
| 20 | 17 |
About Hui Qian
Hui Qian is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 26 papers that have together received 379 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (7 papers), Sparse and Compressive Sensing Techniques (4 papers) and Neural Networks and Applications (3 papers). The work is most often cited by research in Statistical and Nonlinear Physics (111 citations), Computational Mathematics (5 citations) and Computer Vision and Pattern Recognition (104 citations). Hui Qian has collaborated with scholars based in China, United States and Switzerland. Frequent co-authors include Quan Xu, Bocheng Bao, Mo Chen, Jiang Wang, Huagan Wu, Yajuan Yu, Guang Dai, Zhihua Zhang, Paul Loubere and Wuhui Chen. Their work appears in journals such as Analytica Chimica Acta, Biosensors and Bioelectronics and Pattern Recognition.
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.