Shao-Bo Lin
Impact in
- Artificial Intelligence top 2%
- Machine Learning and ELM
- Neural Networks and Applications
- Domain Adaptation and Few-Shot Learning
- Stochastic Gradient Optimization Techniques
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- Face and Expression Recognition
- Advanced Neural Network Applications
- Image and Signal Denoising Methods
Papers in
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- Sparse and Compressive Sensing Techniques 23
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- Neural Networks and Applications 20
- Machine Learning and ELM 12
- Domain Adaptation and Few-Shot Learning 7
- Co-authors
- Ding‐Xuan Zhou (13 shared papers)Zongben Xu (10 shared papers)Jian Fang (5 shared papers)Jinshan Zeng (12 shared papers)Xia Liu (2 shared papers)Zheng-Chu Guo (3 shared papers)Zongben Xu (7 shared papers)Xiangyu Chang (8 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (6 papers)Journal of Machine Learning Research (5 papers)IEEE Transactions on Cybernetics (5 papers)Neural Networks (4 papers)Neurocomputing (2 papers)
- Partner nations
- ChinaHong KongUnited States
In The Last Decade
Shao-Bo Lin
57 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 690
- Computer Vision and Pattern Recognition 413
- Computational Mechanics 247
- Statistics and Probability 92
- Computational Mathematics 5
Countries citing papers authored by Shao-Bo Lin
This map shows the geographic impact of Shao-Bo Lin'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 Shao-Bo Lin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shao-Bo Lin more than expected).
Fields of papers citing papers by Shao-Bo Lin
This network shows the impact of papers produced by Shao-Bo Lin. 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 Shao-Bo Lin. The network helps show where Shao-Bo Lin may publish in the future.
Co-authors
The 25 scholars most cited alongside Shao-Bo Lin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 200 | |
| 2 | 2014 | 176 | |
| 3 | 2014 | 118 | |
| 4 | 2017 | 72 | |
| 5 | 2017 | 54 | |
| 6 | Distributed Learning with Regularized Least Squares | 2017 | 42 |
| 7 | Distributed semi-supervised learning with kernel ridge regression | 2017 | 40 |
| 8 | 2018 | 37 | |
| 9 | 2016 | 32 | |
| 10 | 2020 | 30 | |
| 11 | 2019 | 26 | |
| 12 | 2017 | 23 | |
| 13 | 2010 | 22 | |
| 14 | 2013 | 21 | |
| 15 | 2017 | 20 | |
| 16 | 2018 | 20 | |
| 17 | 2017 | 20 | |
| 18 | 2021 | 15 | |
| 19 | 2018 | 14 | |
| 20 | 2022 | 14 |
About Shao-Bo Lin
Shao-Bo Lin is a scholar working on Computational Mechanics, Artificial Intelligence, Computer Vision and Pattern Recognition, Mathematical Physics and Statistical and Nonlinear Physics, having authored 60 papers that have together received 1.2k indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (23 papers), Neural Networks and Applications (20 papers), Image and Signal Denoising Methods (12 papers), Machine Learning and ELM (12 papers), Face and Expression Recognition (8 papers), Numerical methods in inverse problems (8 papers), Domain Adaptation and Few-Shot Learning (7 papers) and Model Reduction and Neural Networks (7 papers). The work is most often cited by research in Artificial Intelligence (690 citations), Computer Vision and Pattern Recognition (413 citations), Computational Mechanics (247 citations), Statistics and Probability (92 citations) and Computational Mathematics (5 citations). Shao-Bo Lin has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Ding‐Xuan Zhou, Zongben Xu, Jian Fang, Jinshan Zeng, Xia Liu, Zheng-Chu Guo, Zongben Xu, Xiangyu Chang, Long Fei Chen and Hangbin Wu. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Journal of Machine Learning Research, IEEE Transactions on Cybernetics, Neural Networks and Neurocomputing.
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.