Xiaohan Chen
Impact in
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- Privacy-Preserving Technologies in Data
- Stochastic Gradient Optimization Techniques
- Cryptography and Data Security
- Domain Adaptation and Few-Shot Learning
- Internet Traffic Analysis and Secure E-voting
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- Advanced Neural Network Applications
Papers in
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- Stochastic Gradient Optimization Techniques 3
- Privacy-Preserving Technologies in Data 3
- Domain Adaptation and Few-Shot Learning 2
- Adversarial Robustness in Machine Learning 2
- Machine Learning and Data Classification 1
- Cryptography and Data Security 1
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- Advanced Neural Network Applications 3
- Co-authors
- Zhangyang Wang (7 shared papers)Haris Vikalo (1 shared paper)Yang Katie Zhao (3 shared papers)Yuan Xie (1 shared paper)Yue Wang (2 shared papers)Yonggan Fu (2 shared papers)Chaojian Li (2 shared papers)Yingyan Lin (3 shared papers)
- Journals
- IEEE Transactions on Neural Networks and Learning Systems (1 paper)Advances in Education Humanities and Social Science Research (1 paper)Rare & Special e-Zone (The Hong Kong University of Science and Technology) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United StatesMacaoChina
In The Last Decade
Xiaohan Chen
7 papers receiving 128 citations
Peers
Comparison fields: 5 of 33
- Artificial Intelligence 100
- Computer Vision and Pattern Recognition 31
- Neurology 7
- Hardware and Architecture 6
- Computer Science Applications 3
Countries citing papers authored by Xiaohan Chen
This map shows the geographic impact of Xiaohan Chen'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 Xiaohan Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaohan Chen more than expected).
Fields of papers citing papers by Xiaohan Chen
This network shows the impact of papers produced by Xiaohan Chen. 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 Xiaohan Chen. The network helps show where Xiaohan Chen may publish in the future.
Co-authors
The 22 scholars most cited alongside Xiaohan Chen, 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 | 2022 | 70 | |
| 2 | 2020 | 32 | |
| 3 | 2023 | 15 | |
| 4 | 2021 | 7 | |
| 5 | 2022 | 2 | |
| 6 | E2-Train: Energy-Efficient Deep Network Training with Data-, Model-, and Algorithm-Level Saving. | 2019 | 1 |
| 7 | 2022 | 1 | |
| 8 | 2022 | 0 |
About Xiaohan Chen
Xiaohan Chen is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Developmental and Educational Psychology and Building and Construction, having authored 8 papers that have together received 128 indexed citations. Recurring topics across this work include Stochastic Gradient Optimization Techniques (3 papers), Privacy-Preserving Technologies in Data (3 papers), Advanced Neural Network Applications (3 papers), Domain Adaptation and Few-Shot Learning (2 papers), Adversarial Robustness in Machine Learning (2 papers), Machine Learning and Data Classification (1 paper), Chronic Disease Management Strategies (1 paper) and Cryptography and Data Security (1 paper). The work is most often cited by research in Artificial Intelligence (100 citations), Computer Vision and Pattern Recognition (31 citations), Neurology (7 citations), Hardware and Architecture (6 citations) and Computer Science Applications (3 citations). Xiaohan Chen has collaborated with scholars based in United States, Macao and China. Frequent co-authors include Zhangyang Wang, Haris Vikalo, Yang Katie Zhao, Yuan Xie, Yue Wang, Yonggan Fu, Chaojian Li, Yingyan Lin, Haoran You and Myungjin Lee. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Advances in Education Humanities and Social Science Research, Rare & Special e-Zone (The Hong Kong University of Science and Technology) 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.