Edward W. Wild
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- Face and Expression Recognition 3
- Artificial Intelligence top 2%
- Machine Learning and Data Classification 3
- Neural Networks and Applications 2
- Machine Learning and Algorithms 2
- Privacy-Preserving Technologies in Data 2
- Gaussian Processes and Bayesian Inference 2
- Media Technology top 5%
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- Advanced Multi-Objective Optimization Algorithms 2
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- Statistical Methods and Inference 2
- Co-authors
- O. L. MangasarianJude ShavlikGlenn FungRichard MaclinLisa TorreyTrevor WalkerNora Naumann‐BartschSven Dittrich
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceControl and Systems Engineering
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)Journal of Machine Learning Research (1 paper)Journal of Optimization Theory and Applications (1 paper)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Edward W. Wild
11 papers receiving 913 citations
Hit Papers
Peers
Comparison fields: 5 of 81
- Computer Vision and Pattern Recognition 606
- Artificial Intelligence 620
- Control and Systems Engineering 248
- Media Technology 77
- Computational Mathematics 5
Countries citing papers authored by Edward W. Wild
This map shows the geographic impact of Edward W. Wild'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 Edward W. Wild with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward W. Wild more than expected).
Fields of papers citing papers by Edward W. Wild
This network shows the impact of papers produced by Edward W. Wild. 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 Edward W. Wild. The network helps show where Edward W. Wild may publish in the future.
Co-authorship network
The 12 scholars most cited alongside Edward W. Wild, 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 | 2025 | 0 | |
| 2 | 2011 | 1 | |
| 3 | 2009 | 5 | |
| 4 | Privacy-Preserving Classification of Horizontally Partitioned Data via Random Kernels. | 2008 | 33 |
| 5 | 2008 | 32 | |
| 6 | 2008 | 50 | |
| 7 | Optimization-based machine learning and data mining | 2008 | 1 |
| 8 | Refining rules incorporated into knowledge-based support vector learners via successive linear programming | 2007 | 6 |
| 9 | 2007 | 74 | |
| 10 | Multisurface proximal support vector machine classification via generalized eigenvaluesbreakdown → | 2006 | 620 |
| 11 | Giving advice about preferred actions to reinforcement learners via knowledge-based kernel regression | 2005 | 61 |
| 12 | 2004 | 54 | |
| 13 | Feature Selection in k-Median Clustering | 2004 | 7 |
About Edward W. Wild
Edward W. Wild is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 13 papers that have together received 944 indexed citations. Recurring topics across this work include Face and Expression Recognition (3 papers), Machine Learning and Data Classification (3 papers), Neural Networks and Applications (2 papers), Advanced Multi-Objective Optimization Algorithms (2 papers), Machine Learning and Algorithms (2 papers), Privacy-Preserving Technologies in Data (2 papers), Statistical Methods and Inference (2 papers) and Gaussian Processes and Bayesian Inference (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (606 citations), Artificial Intelligence (620 citations) and Control and Systems Engineering (248 citations). Edward W. Wild has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include O. L. Mangasarian, Jude Shavlik, Glenn Fung, Richard Maclin, Lisa Torrey, Trevor Walker, Nora Naumann‐Bartsch, Sven Dittrich, Felix Huber and Ferdinand Knieling. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Journal of Machine Learning Research and Journal of Optimization Theory 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.