Qi Cai
- Artificial Intelligence
- Management Science and Operations Research
- Electrical and Electronic Engineering
- Computational Theory and Mathematics
- Computer Networks and Communications
- Co-authors
- Zhuoran YangZhaoran WangChi JinJason D. LeeMin ZhangMengjuan MuWenbiao WangPing Liang
- Topics
- Reinforcement Learning in Robotics (4 papers)Advanced Vision and Imaging (2 papers)Machine Learning and ELM (2 papers)
- Cited by
- Management Science and Operations ResearchArtificial IntelligenceComputational Theory and Mathematics
- Journals
- Mathematics of Operations ResearchIEEE Journal of Biomedical and Health InformaticsIEEE Robotics and Automation Letters
- Partner nations
- ChinaUnited States
In The Last Decade
Qi Cai
11 papers receiving 90 citations
Peers
Comparison fields: 5 of 37
- Artificial Intelligence 57
- Management Science and Operations Research 27
- Electrical and Electronic Engineering 23
- Computational Theory and Mathematics 19
- Computer Networks and Communications 15
Countries citing papers authored by Qi Cai
This map shows the geographic impact of Qi Cai'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 Qi Cai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qi Cai more than expected).
Fields of papers citing papers by Qi Cai
This network shows the impact of papers produced by Qi Cai. 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 Qi Cai. The network helps show where Qi Cai may publish in the future.
Co-authorship network of co-authors of Qi Cai
This figure shows the co-authorship network connecting the top 25 collaborators of Qi Cai. A scholar is included among the top collaborators of Qi Cai 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 Qi Cai. Qi Cai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 6 | |
| 3 | 6 | |
| 4 | Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory. | 1 |
| 5 | Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate | 4 |
| 6 | Provably Efficient Exploration in Policy Optimization | 20 |
| 7 | Neural proximal/trust region policy optimization attains globally optimal policy | 23 |
| 8 | Neural Trust Region/Proximal Policy Optimization Attains Globally Optimal Policy | 22 |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 8 |
About Qi Cai
Qi Cai is a scholar working on Artificial Intelligence, Aerospace Engineering and Radiation, having authored 12 papers that have together received 94 indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (4 papers), Advanced Vision and Imaging (2 papers) and Machine Learning and ELM (2 papers). The work is most often cited by research in Management Science and Operations Research (27 citations), Artificial Intelligence (57 citations) and Computational Theory and Mathematics (19 citations). Qi Cai has collaborated with scholars based in China and United States. Frequent co-authors include Zhuoran Yang, Zhaoran Wang, Zhaoran Wang, Chi Jin, Jason D. Lee, Min Zhang, Mengjuan Mu, Wenbiao Wang, Ping Liang and Yong Xu. Their work appears in journals such as Mathematics of Operations Research, IEEE Journal of Biomedical and Health Informatics and IEEE Robotics and Automation Letters.
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.