Burr Settles
Impact in
- Artificial Intelligence top 0.1%
- Machine Learning and Algorithms
- Topic Modeling
- Machine Learning and Data Classification
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Algorithms and Data Compression
- Data Stream Mining Techniques
- Computational Mathematics top 2%
Papers in
-
- Machine Learning and Algorithms 15
- Topic Modeling 14
- Natural Language Processing Techniques 12
- Machine Learning and Data Classification 9
- Algorithms and Data Compression 4
- Data Stream Mining Techniques 4
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- Biomedical Text Mining and Ontologies 6
- Co-authors
- Mark Craven (8 shared papers)Tom M. Mitchell (2 shared papers)J. Andrew Carlson (1 shared paper)Justin Betteridge (1 shared paper)Estevam Hruschka (1 shared paper)Bryan Kisiel (1 shared paper)Soumya Ray (1 shared paper)Brendan Meeder (2 shared papers)
- Journals
- Synthesis lectures on artificial intelligence and machine learning (4 papers)ACS Chemical Biology (1 paper)Transactions of the Association for Computational Linguistics (1 paper)Applied Psychological Measurement (1 paper)Computer applications in the biosciences (1 paper)
- Partner nations
- United StatesGermanyFinland
In The Last Decade
Burr Settles
39 papers receiving 8.5k citations
Burr Settles's Hit Papers
Peers
Comparison fields: 5 of 193
- Artificial Intelligence 6.8k
- Computational Mathematics 52
- Computer Science Applications 459
- Computer Vision and Pattern Recognition 1.5k
- Management Science and Operations Research 641
Countries citing papers authored by Burr Settles
This map shows the geographic impact of Burr Settles'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 Burr Settles with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Burr Settles more than expected).
Fields of papers citing papers by Burr Settles
This network shows the impact of papers produced by Burr Settles. 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 Burr Settles. The network helps show where Burr Settles may publish in the future.
Co-authors
The 25 scholars most cited alongside Burr Settles, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Active Learning Literature Survey Hit paper breakdown → | 2009 | 3257 |
| 2 | Toward an Architecture for Never-Ending Language Learning Hit paper breakdown → | 2010 | 1397 |
| 3 | Active Learning Hit paper breakdown → | 2012 | 742 |
| 4 | An analysis of active learning strategies for sequence labeling tasks Hit paper breakdown → | 2008 | 707 |
| 5 | Active Learning Hit paper breakdown → | 2012 | 457 |
| 6 | 2004 | 419 | |
| 7 | 2005 | 359 | |
| 8 | Multiple-Instance Active Learning | 2007 | 340 |
| 9 | Active Learning Hit paper breakdown → | 2012 | 338 |
| 10 | Active Learning with Real Annotation Costs | 2008 | 144 |
| 11 | 2016 | 130 | |
| 12 | Closing the Loop: Fast, Interactive Semi-Supervised Annotation With Queries on Features and Instances | 2011 | 115 |
| 13 | From Theories to Queries: Active Learning in Practice | 2011 | 109 |
| 14 | 2009 | 107 | |
| 15 | 2010 | 66 | |
| 16 | 2020 | 60 | |
| 17 | 2018 | 51 | |
| 18 | Curious machines: active learning with structured instances | 2008 | 38 |
| 19 | 2015 | 30 | |
| 20 | 2010 | 25 |
About Burr Settles
Burr Settles is a scholar working on Artificial Intelligence, Molecular Biology, Communication, Computer Vision and Pattern Recognition and Sociology and Political Science, having authored 40 papers that have together received 9.1k indexed citations. Recurring topics across this work include Machine Learning and Algorithms (15 papers), Topic Modeling (14 papers), Natural Language Processing Techniques (12 papers), Machine Learning and Data Classification (9 papers), Biomedical Text Mining and Ontologies (6 papers), Algorithms and Data Compression (4 papers), Data Stream Mining Techniques (4 papers) and Knowledge Management and Sharing (2 papers). The work is most often cited by research in Artificial Intelligence (6.8k citations), Computational Mathematics (52 citations), Computer Science Applications (459 citations), Computer Vision and Pattern Recognition (1.5k citations) and Management Science and Operations Research (641 citations). Burr Settles has collaborated with scholars based in United States, Germany and Finland. Frequent co-authors include Mark Craven, Tom M. Mitchell, J. Andrew Carlson, Justin Betteridge, Estevam Hruschka, Bryan Kisiel, Soumya Ray, Brendan Meeder, Lewis A. Friedland and Andrew McCallum. Their work appears in journals such as Synthesis lectures on artificial intelligence and machine learning, ACS Chemical Biology, Transactions of the Association for Computational Linguistics, Applied Psychological Measurement and Computer applications in the biosciences.
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.