Po-Wei Wang
Impact in
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- Topic Modeling
- Advanced Graph Neural Networks
- Natural Language Processing Techniques
- Imbalanced Data Classification Techniques
- Data Stream Mining Techniques
- Bayesian Modeling and Causal Inference
Papers in
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- Bayesian Modeling and Causal Inference 3
- Machine Learning and Algorithms 2
- Topic Modeling 2
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- Advanced Bandit Algorithms Research 2
- Co-authors
- J. Zico Kolter (6 shared papers)Chih‐Jen Lin (3 shared papers)Daria Stepanova (1 shared paper)Csaba Domokos (1 shared paper)Ching-pei Lee (2 shared papers)Inderjit S. Dhillon (1 shared paper)X.-G. Xia (1 shared paper)Andrew Zhai (1 shared paper)
- Journals
- Mathematical Programming Computation (1 paper)MRS Communications (1 paper)Journal of Machine Learning Research (1 paper)International Conference on Learning Representations (1 paper)International ACM SIGIR Conference on Research and Development in Information Retrieval (1 paper)
- Partner nations
- United StatesTaiwanGermany
In The Last Decade
Po-Wei Wang
10 papers receiving 32 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 26
- Computer Vision and Pattern Recognition 8
- Information Systems 8
- Management Science and Operations Research 3
- Computer Networks and Communications 5
Countries citing papers authored by Po-Wei Wang
This map shows the geographic impact of Po-Wei Wang'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 Po-Wei Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Po-Wei Wang more than expected).
Fields of papers citing papers by Po-Wei Wang
This network shows the impact of papers produced by Po-Wei Wang. 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 Po-Wei Wang. The network helps show where Po-Wei Wang may publish in the future.
Co-authors
The 10 scholars most cited alongside Po-Wei Wang, 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 | Differentiable learning of numerical rules in knowledge graphs | 2020 | 11 |
| 2 | Support Vector Machines. | 2014 | 7 |
| 3 | Realtime query completion via deep language models | 2018 | 4 |
| 4 | 2023 | 4 | |
| 5 | Epigraph projections for fast general convex programming | 2016 | 2 |
| 6 | The Common-directions Method for Regularized Empirical Risk Minimization | 2019 | 2 |
| 7 | 2019 | 2 | |
| 8 | 2023 | 1 | |
| 9 | 2020 | 1 | |
| 10 | 2020 | 1 | |
| 11 | 2024 | 1 | |
| 12 | 2022 | 0 |
About Po-Wei Wang
Po-Wei Wang is a scholar working on Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 12 papers that have together received 36 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (3 papers), Advanced Bandit Algorithms Research (2 papers), Machine Learning and Algorithms (2 papers), Recommender Systems and Techniques (2 papers), Sparse and Compressive Sensing Techniques (2 papers), Topic Modeling (2 papers), Heusler alloys: electronic and magnetic properties (1 paper) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Artificial Intelligence (26 citations), Computer Vision and Pattern Recognition (8 citations), Information Systems (8 citations), Management Science and Operations Research (3 citations) and Computer Networks and Communications (5 citations). Po-Wei Wang has collaborated with scholars based in United States, Taiwan and Germany. Frequent co-authors include J. Zico Kolter, Chih‐Jen Lin, Daria Stepanova, Csaba Domokos, Ching-pei Lee, Inderjit S. Dhillon, X.-G. Xia, Andrew Zhai, Jiajing Xu and Cheng‐Lun Hsin. Their work appears in journals such as Mathematical Programming Computation, MRS Communications, Journal of Machine Learning Research, International Conference on Learning Representations and International ACM SIGIR Conference on Research and Development in Information Retrieval.
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.