Chih‐Wei Hsu
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Information Systems top 5%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Chih‐Jen LinJiawei HanXifeng YanHong ChengCarl F. FalkKosuke TakemuraRuoyun HuangYixin Chen
- Topics
- Advanced Bandit Algorithms Research (4 papers)Reinforcement Learning in Robotics (3 papers)Recommender Systems and Techniques (3 papers)
- Partner nations
- United StatesTaiwanCanada
In The Last Decade
Chih‐Wei Hsu
16 papers receiving 743 citations
Hit Papers
Peers
Comparison fields: 5 of 117
- Artificial Intelligence 338
- Computer Vision and Pattern Recognition 208
- Information Systems 189
- Signal Processing 111
- Computer Networks and Communications 86
Countries citing papers authored by Chih‐Wei Hsu
This map shows the geographic impact of Chih‐Wei Hsu'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 Chih‐Wei Hsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chih‐Wei Hsu more than expected).
Fields of papers citing papers by Chih‐Wei Hsu
This network shows the impact of papers produced by Chih‐Wei Hsu. 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 Chih‐Wei Hsu. The network helps show where Chih‐Wei Hsu may publish in the future.
Co-authorship network of co-authors of Chih‐Wei Hsu
This figure shows the co-authorship network connecting the top 25 collaborators of Chih‐Wei Hsu. A scholar is included among the top collaborators of Chih‐Wei Hsu 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 Chih‐Wei Hsu. Chih‐Wei Hsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | Differentiable Meta-Learning in Contextual Bandits. | 1 |
| 6 | Differentiable Meta-Learning of Bandit Policies. | 4 |
| 7 | 16 | |
| 8 | 6 | |
| 9 | 15 | |
| 10 | 29 | |
| 11 | 1 | |
| 12 | 13 | |
| 13 | 3 | |
| 14 | 1 | |
| 15 | Constraint partitioning for solving planning problems with trajectory constraints and goal preferences | 25 |
| 16 | 223 | |
| 17 | A comparison of methods for multiclass support vector machinesbreakdown → | 459 |
About Chih‐Wei Hsu
Chih‐Wei Hsu is a scholar working on Neuropsychology and Physiological Psychology, Management Science and Operations Research and Artificial Intelligence, having authored 17 papers that have together received 801 indexed citations. Recurring topics across this work include Advanced Bandit Algorithms Research (4 papers), Reinforcement Learning in Robotics (3 papers) and Recommender Systems and Techniques (3 papers). The work is most often cited by research in Artificial Intelligence (338 citations), Signal Processing (111 citations) and Computer Vision and Pattern Recognition (208 citations). Chih‐Wei Hsu has collaborated with scholars based in United States, Taiwan and Canada. Frequent co-authors include Chih‐Jen Lin, Jiawei Han, Xifeng Yan, Hong Cheng, Carl F. Falk, Kosuke Takemura, Ruoyun Huang, Yixin Chen, Steven J. Heine and Benjamin W. Wah. Their work appears in journals such as Journal of Personality, Sustainability and Multimedia Tools and 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.