Yanyao Shen
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- Cooperative Communication and Network Coding 3
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- Topic Modeling 2
- Natural Language Processing Techniques 2
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- Advanced Wireless Network Optimization 4
- Advanced MIMO Systems Optimization 3
- Energy Harvesting in Wireless Networks 1
- Power Line Communications and Noise 1
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- Sparse and Compressive Sensing Techniques 1
- Cited by
- Computer Networks and CommunicationsComputer Vision and Pattern RecognitionArtificial Intelligence
- Journals
- IEEE Transactions on Wireless Communications (2 papers)IEEE Wireless Communications (1 paper)International Conference on Machine Learning (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Yanyao Shen
10 papers receiving 194 citations
Peers
Comparison fields: 5 of 35
- Computer Networks and Communications 99
- Computer Vision and Pattern Recognition 44
- Artificial Intelligence 63
- Computational Mathematics 1
- Electrical and Electronic Engineering 87
Countries citing papers authored by Yanyao Shen
This map shows the geographic impact of Yanyao Shen'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 Yanyao Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yanyao Shen more than expected).
Fields of papers citing papers by Yanyao Shen
This network shows the impact of papers produced by Yanyao Shen. 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 Yanyao Shen. The network helps show where Yanyao Shen may publish in the future.
Co-authorship network
The 19 scholars most cited alongside Yanyao Shen, 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 | Extreme Multi-label Classification from Aggregated Labels | 2020 | 1 |
| 2 | Learning with Bad Training Data via Iterative Trimmed Loss Minimization | 2019 | 20 |
| 3 | Deep Active Learning for Named Entity Recognition. | 2018 | 18 |
| 4 | 2018 | 18 | |
| 5 | 2016 | 50 | |
| 6 | Normalized Spectral Map Synchronization | 2016 | 24 |
| 7 | 2016 | 10 | |
| 8 | 2015 | 47 | |
| 9 | 2015 | 2 | |
| 10 | 2014 | 11 |
About Yanyao Shen
Yanyao Shen is a scholar working on Computer Networks and Communications, Artificial Intelligence and Electrical and Electronic Engineering, having authored 10 papers that have together received 201 indexed citations. Recurring topics across this work include Advanced Wireless Network Optimization (4 papers), Advanced MIMO Systems Optimization (3 papers), Cooperative Communication and Network Coding (3 papers), Topic Modeling (2 papers), Natural Language Processing Techniques (2 papers), Energy Harvesting in Wireless Networks (1 paper), Power Line Communications and Noise (1 paper) and Sparse and Compressive Sensing Techniques (1 paper). The work is most often cited by research in Computer Networks and Communications (99 citations), Computer Vision and Pattern Recognition (44 citations) and Artificial Intelligence (63 citations). Yanyao Shen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Chunxiao Jiang, Yong Ren, Tony Q. S. Quek, Sujay Sanghavi, Lei Xu, Zhu Han, Nati Srebro, Qixing Huang, Zachary C. Lipton and Hyokun Yun. Their work appears in journals such as IEEE Transactions on Wireless Communications, IEEE Wireless Communications, International Conference on Machine Learning, CaltechAUTHORS (California Institute of Technology) and Neural Information Processing Systems.
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.