Qiang Yang
Impact in
- Artificial Intelligence top 0.01%
- Privacy-Preserving Technologies in Data
- Domain Adaptation and Few-Shot Learning
- Topic Modeling
- Text and Document Classification Technologies
- Machine Learning and ELM
- Anomaly Detection Techniques and Applications
- Computer Vision and Pattern Recognition top 0.02%
- Face and Expression Recognition
Papers in
-
- Privacy-Preserving Technologies in Data 77
- Text and Document Classification Technologies 65
- AI-based Problem Solving and Planning 60
- Domain Adaptation and Few-Shot Learning 53
- Topic Modeling 49
-
- Recommender Systems and Techniques 89
- Data Mining Algorithms and Applications 50
- Web Data Mining and Analysis 39
- Co-authors
- Sinno Jialin Pan (31 shared papers)Yu Zhang (19 shared papers)Tianjian Chen (16 shared papers)Yang Liu (11 shared papers)Yongxin Tong (5 shared papers)Yong Yu (21 shared papers)Gui-Rong Xue (22 shared papers)Wenyuan Dai (21 shared papers)
- Journals
- IEEE Transactions on Knowledge and Data Engineering (24 papers)ACM Transactions on Intelligent Systems and Technology (19 papers)IEEE Intelligent Systems (18 papers)Artificial Intelligence (17 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (8 papers)
- Partner nations
- Hong KongChinaUnited States
In The Last Decade
Qiang Yang
798 papers receiving 61.8k citations
Qiang Yang's Hit Papers
Peers
Comparison fields: 5 of 236
- Artificial Intelligence 32.2k
- Computer Vision and Pattern Recognition 13.7k
- Computational Mathematics 352
- Information Systems 11.2k
- Signal Processing 4.7k
Countries citing papers authored by Qiang Yang
This map shows the geographic impact of Qiang Yang'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 Qiang Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qiang Yang more than expected).
Fields of papers citing papers by Qiang Yang
This network shows the impact of papers produced by Qiang Yang. 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 Qiang Yang. The network helps show where Qiang Yang may publish in the future.
Co-authors
The 25 scholars most cited alongside Qiang Yang, 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 834 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | A Survey on Transfer Learning Hit paper breakdown → | 2009 | 15630 |
| 2 | Top 10 algorithms in data mining Hit paper breakdown → | 2007 | 3928 |
| 3 | Federated Machine Learning Hit paper breakdown → | 2019 | 3514 |
| 4 | Graph Embedding and Extensions: A General Framework for Dimensionality Reduction Hit paper breakdown → | 2006 | 2245 |
| 5 | Federated Learning in Mobile Edge Networks: A Comprehensive Survey Hit paper breakdown → | 2020 | 1660 |
| 6 | A Survey on Multi-Task Learning Hit paper breakdown → | 2021 | 1368 |
| 7 | A Survey on Evaluation of Large Language Models Hit paper breakdown → | 2024 | 1227 |
| 8 | Boosting for transfer learning Hit paper breakdown → | 2007 | 1198 |
| 9 | An overview of multi-task learning Hit paper breakdown → | 2017 | 731 |
| 10 | One-Class Collaborative Filtering Hit paper breakdown → | 2008 | 684 |
| 11 | Spatiotemporal Multi-Graph Convolution Network for Ride-Hailing Demand Forecasting Hit paper breakdown → | 2019 | 612 |
| 12 | 10 CHALLENGING PROBLEMS IN DATA MINING RESEARCH Hit paper breakdown → | 2006 | 592 |
| 13 | Cross-domain sentiment classification via spectral feature alignment Hit paper breakdown → | 2010 | 511 |
| 14 | 2005 | 483 | |
| 15 | Collaborative location and activity recommendations with GPS history data Hit paper breakdown → | 2010 | 474 |
| 16 | Transfer learning via dimensionality reduction Hit paper breakdown → | 2008 | 412 |
| 17 | A Secure Federated Transfer Learning Framework Hit paper breakdown → | 2020 | 410 |
| 18 | Proceedings of the 24th International Conference on Artificial Intelligence Hit paper breakdown → | 2015 | 383 |
| 19 | A Full Dive Into Realizing the Edge-Enabled Metaverse: Visions, Enabling Technologies, and Challenges Hit paper breakdown → | 2022 | 378 |
| 20 | 2010 | 366 |
About Qiang Yang
Qiang Yang is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Signal Processing, having authored 834 papers that have together received 64.2k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (89 papers), Privacy-Preserving Technologies in Data (77 papers), Text and Document Classification Technologies (65 papers), AI-based Problem Solving and Planning (60 papers), Domain Adaptation and Few-Shot Learning (53 papers), Data Mining Algorithms and Applications (50 papers), Topic Modeling (49 papers) and Web Data Mining and Analysis (39 papers). The work is most often cited by research in Artificial Intelligence (32.2k citations), Computer Vision and Pattern Recognition (13.7k citations), Computational Mathematics (352 citations), Information Systems (11.2k citations) and Signal Processing (4.7k citations). Qiang Yang has collaborated with scholars based in Hong Kong, China and United States. Frequent co-authors include Sinno Jialin Pan, Yu Zhang, Tianjian Chen, Yang Liu, Yongxin Tong, Yong Yu, Gui-Rong Xue, Wenyuan Dai, Xindong Wu and Shuicheng Yan. Their work appears in journals such as IEEE Transactions on Knowledge and Data Engineering, ACM Transactions on Intelligent Systems and Technology, IEEE Intelligent Systems, Artificial Intelligence and IEEE Transactions on Pattern Analysis and Machine 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.