David Vickrey
Impact in
- Artificial Intelligence top 5%
- Natural Language Processing Techniques
- Topic Modeling
- Text Readability and Simplification
- Domain Adaptation and Few-Shot Learning
- Speech and dialogue systems
- Semantic Web and Ontologies
- Machine Learning and Data Classification
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- Game Theory and Applications
Papers in
-
- Topic Modeling 5
- Natural Language Processing Techniques 5
- Domain Adaptation and Few-Shot Learning 2
- Machine Learning and Data Classification 2
- Text Readability and Simplification 2
- Machine Learning and Algorithms 2
- Text and Document Classification Technologies 2
- Co-authors
- Daphne Koller (9 shared papers)Su-In Lee (1 shared paper)Marc Teyssier (1 shared paper)Cliff Chiung-Yu Lin (1 shared paper)William Choi (1 shared paper)Jason Turner-Maier (1 shared paper)Aman Kumar (1 shared paper)John C. Duchi (1 shared paper)
- Journals
- Ars Combinatoria (1 paper)International Conference on Machine Learning (1 paper)National Conference on Artificial Intelligence (1 paper)arXiv (Cornell University) (1 paper)Meeting of the Association for Computational Linguistics (2 papers)
- Partner nations
- United StatesFranceSpain
In The Last Decade
David Vickrey
10 papers receiving 418 citations
Peers
Comparison fields: 5 of 57
- Artificial Intelligence 373
- Management Science and Operations Research 59
- Computer Science Applications 17
- Computer Vision and Pattern Recognition 59
- Information Systems 32
Countries citing papers authored by David Vickrey
This map shows the geographic impact of David Vickrey'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 David Vickrey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Vickrey more than expected).
Fields of papers citing papers by David Vickrey
This network shows the impact of papers produced by David Vickrey. 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 David Vickrey. The network helps show where David Vickrey may publish in the future.
Co-authors
The 9 scholars most cited alongside David Vickrey, 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 | 2007 | 124 | |
| 2 | 2005 | 122 | |
| 3 | Sentence Simplification for Semantic Role Labeling | 2008 | 79 |
| 4 | 2002 | 68 | |
| 5 | 2008 | 24 | |
| 6 | Non-Local Contrastive Objectives | 2010 | 14 |
| 7 | 2008 | 10 | |
| 8 | 2012 | 9 | |
| 9 | An Active Learning Approach to Finding Related Terms | 2010 | 4 |
| 10 | k-equitable labelings of complete bipartite and multipartite graphs. | 1999 | 1 |
About David Vickrey
David Vickrey is a scholar working on Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Management Science and Operations Research, having authored 10 papers that have together received 455 indexed citations. Recurring topics across this work include Topic Modeling (5 papers), Natural Language Processing Techniques (5 papers), Domain Adaptation and Few-Shot Learning (2 papers), Machine Learning and Data Classification (2 papers), Text Readability and Simplification (2 papers), Machine Learning and Algorithms (2 papers), Text and Document Classification Technologies (2 papers) and Graph Labeling and Dimension Problems (1 paper). The work is most often cited by research in Artificial Intelligence (373 citations), Management Science and Operations Research (59 citations), Computer Science Applications (17 citations), Computer Vision and Pattern Recognition (59 citations) and Information Systems (32 citations). David Vickrey has collaborated with scholars based in United States, France and Spain. Frequent co-authors include Daphne Koller, Su-In Lee, Marc Teyssier, Cliff Chiung-Yu Lin, William Choi, Jason Turner-Maier, Aman Kumar, John C. Duchi and Varun Ganapathi. Their work appears in journals such as Ars Combinatoria, International Conference on Machine Learning, National Conference on Artificial Intelligence, arXiv (Cornell University) and Meeting of the Association for Computational Linguistics.
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.