Zhi‐Hua Zhou
- Artificial Intelligence top 0.01%
- Computer Vision and Pattern Recognition top 0.02%
- Information Systems top 0.05%
- Signal Processing top 0.05%
- Computer Networks and Communications top 0.2%
- Topics
- Machine Learning and Data Classification (91 papers)Machine Learning and Algorithms (72 papers)Text and Document Classification Technologies (71 papers)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Zhi‐Hua Zhou
387 papers receiving 37.0k citations
Hit Papers
Peers
Comparison fields: 5 of 227
- Artificial Intelligence 22.7k
- Computer Vision and Pattern Recognition 13.3k
- Information Systems 4.9k
- Signal Processing 4.1k
- Computer Networks and Communications 3.1k
Countries citing papers authored by Zhi‐Hua Zhou
This map shows the geographic impact of Zhi‐Hua Zhou'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 Zhi‐Hua Zhou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Zhi‐Hua Zhou more than expected).
Fields of papers citing papers by Zhi‐Hua Zhou
This network shows the impact of papers produced by Zhi‐Hua Zhou. 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 Zhi‐Hua Zhou. The network helps show where Zhi‐Hua Zhou may publish in the future.
Co-authorship network of co-authors of Zhi‐Hua Zhou
This figure shows the co-authorship network connecting the top 25 collaborators of Zhi‐Hua Zhou. A scholar is included among the top collaborators of Zhi‐Hua Zhou 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 Zhi‐Hua Zhou. Zhi‐Hua Zhou is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | Reducing the uncertainty in estimating soil microbial-derived carbon storagebreakdown → | 68 |
| 3 | 3 | |
| 4 | 4 | |
| 5 | Dynamic Regret of Convex and Smooth Functions. | 2 |
| 6 | 49 | |
| 7 | Unorganized Malicious Attacks Detection | 2 |
| 8 | Transductive optimization of top k precision | 6 |
| 9 | Statistical Unfolded Logic Learning | 1 |
| 10 | Active learning from crowds with unsure option | 31 |
| 11 | Learning with Augmented Multi-Instance View | 1 |
| 12 | 5 | |
| 13 | 1 | |
| 14 | Co-Training with Insufficient Views | 20 |
| 15 | 35 | |
| 16 | Towards Making Unlabeled Data Never Hurt | 58 |
| 17 | A New Analysis of Co-Training | 126 |
| 18 | Constraint projections for ensemble learning | 20 |
| 19 | Multi-label learning by instance differentiation | 52 |
| 20 | Semi-supervised learning with very few labeled training examples | 91 |
About Zhi‐Hua Zhou
Zhi‐Hua Zhou is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing, having authored 399 papers that have together received 38.5k indexed citations. Recurring topics across this work include Machine Learning and Data Classification (91 papers), Machine Learning and Algorithms (72 papers) and Text and Document Classification Technologies (71 papers). The work is most often cited by research in Artificial Intelligence (22.7k citations), Computer Vision and Pattern Recognition (13.3k citations) and Signal Processing (4.1k citations). Zhi‐Hua Zhou has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Min-Ling Zhang, Kai Ming Ting, Fei Tony Liu, Jianxin Wu, Ji Feng, Wei Tang, Daoqiang Zhang, Xuying Liu, Songcan Chen and Yu-Feng Li. Their work appears in journals such as Proceedings of the National Academy of Sciences, Bioinformatics and PLoS ONE.
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.