Ming Tan
Impact in
- Artificial Intelligence top 5%
- Imbalanced Data Classification Techniques
- Machine Learning and Data Classification
- Machine Learning and Algorithms
- AI-based Problem Solving and Planning
- Reinforcement Learning in Robotics
- Neural Networks and Applications
- Information Systems top 10%
- Data Mining Algorithms and Applications
Papers in
-
- Machine Learning and Data Classification 4
- Machine Learning and Algorithms 4
- Neural Networks and Applications 3
- AI-based Problem Solving and Planning 2
- Anomaly Detection Techniques and Applications 2
-
- Robot Manipulation and Learning 2
- Fault Detection and Control Systems 2
- Co-authors
- Jeffrey C. Schlimmer (3 shared papers)Yanfeng Li (1 shared paper)Ji Li (1 shared paper)Muhammad Ilham Aldika Akbar (1 shared paper)Erry Gumilar Dachlan (1 shared paper)Chien‐Hsing Lu (1 shared paper)
- Journals
- Machine Learning (2 papers)Robotics and Autonomous Systems (1 paper)Computational and Structural Biotechnology Journal (1 paper)IEEE Access (1 paper)Expert Systems with Applications (1 paper)
- Partner nations
- United StatesChinaTaiwan
In The Last Decade
Ming Tan
12 papers receiving 215 citations
Peers
Comparison fields: 5 of 40
- Artificial Intelligence 216
- Information Systems 69
- Computational Theory and Mathematics 32
- Computer Vision and Pattern Recognition 32
- Control and Systems Engineering 28
Countries citing papers authored by Ming Tan
This map shows the geographic impact of Ming Tan'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 Ming Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ming Tan more than expected).
Fields of papers citing papers by Ming Tan
This network shows the impact of papers produced by Ming Tan. 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 Ming Tan. The network helps show where Ming Tan may publish in the future.
Co-authors
The 6 scholars most cited alongside Ming Tan, 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 | 1993 | 87 | |
| 2 | 1993 | 60 | |
| 3 | Two case studies in cost-sensitive concept acquisition | 1990 | 36 |
| 4 | Cost-sensitive reinforcement learning for adaptive classification and control | 1991 | 15 |
| 5 | Cost-sensitive robot learning | 1991 | 15 |
| 6 | 2002 | 10 | |
| 7 | 2024 | 4 | |
| 8 | 2023 | 3 | |
| 9 | 2025 | 3 | |
| 10 | 1991 | 3 | |
| 11 | A cost-sensitive machine learning method for the approach and recognize task | 1993 | 2 |
| 12 | 2003 | 2 | |
| 13 | 1996 | 1 |
About Ming Tan
Ming Tan is a scholar working on Artificial Intelligence, Control and Systems Engineering, Computer Networks and Communications, Ocean Engineering and Health Informatics, having authored 13 papers that have together received 241 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (4 papers), Machine Learning and Algorithms (4 papers), Neural Networks and Applications (3 papers), AI-based Problem Solving and Planning (2 papers), Robot Manipulation and Learning (2 papers), Fault Detection and Control Systems (2 papers), Anomaly Detection Techniques and Applications (2 papers) and Optimization and Search Problems (1 paper). The work is most often cited by research in Artificial Intelligence (216 citations), Information Systems (69 citations), Computational Theory and Mathematics (32 citations), Computer Vision and Pattern Recognition (32 citations) and Control and Systems Engineering (28 citations). Ming Tan has collaborated with scholars based in United States, China and Taiwan. Frequent co-authors include Jeffrey C. Schlimmer, Yanfeng Li, Ji Li, Muhammad Ilham Aldika Akbar, Erry Gumilar Dachlan and Chien‐Hsing Lu. Their work appears in journals such as Machine Learning, Robotics and Autonomous Systems, Computational and Structural Biotechnology Journal, IEEE Access and Expert Systems with Applications.
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.