Hal Daumé
Impact in
- Artificial Intelligence top 0.1%
- Topic Modeling
- Natural Language Processing Techniques
- Domain Adaptation and Few-Shot Learning
- Advanced Text Analysis Techniques
- Text and Document Classification Technologies
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- Multimodal Machine Learning Applications
- Advanced Image and Video Retrieval Techniques
- Face and Expression Recognition
Papers in
-
- Topic Modeling 84
- Natural Language Processing Techniques 65
- Machine Learning and Algorithms 18
- Domain Adaptation and Few-Shot Learning 16
- Machine Learning and Data Classification 13
- Advanced Text Analysis Techniques 11
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- Multimodal Machine Learning Applications 18
- Advanced Image and Video Retrieval Techniques 12
- Co-authors
- Abhishek Kumar (7 shared papers)Daniel Marcu (10 shared papers)Piyush Rai (12 shared papers)Jordan Boyd‐Graber (15 shared papers)Mohit Iyyer (5 shared papers)Lucy Vanderwende (1 shared paper)Katrin Kirchhoff (1 shared paper)Anurag Kumar (1 shared paper)
- Journals
- PLoS ONE (3 papers)International Journal of Computer Vision (2 papers)Proceedings of the ACM on Human-Computer Interaction (2 papers)Computational Linguistics (2 papers)Machine Learning (2 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Hal Daumé
170 papers receiving 8.0k citations
Hal Daumé's Hit Papers
Peers
Comparison fields: 5 of 161
- Artificial Intelligence 5.9k
- Computer Vision and Pattern Recognition 3.2k
- Computational Mathematics 52
- Computer Science Applications 256
- Media Technology 354
Countries citing papers authored by Hal Daumé
This map shows the geographic impact of Hal Daumé'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 Hal Daumé with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hal Daumé more than expected).
Fields of papers citing papers by Hal Daumé
This network shows the impact of papers produced by Hal Daumé. 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 Hal Daumé. The network helps show where Hal Daumé may publish in the future.
Co-authors
The 25 scholars most cited alongside Hal Daumé, 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 179 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Co-regularized Multi-view Spectral Clustering Hit paper breakdown → | 2011 | 696 |
| 2 | Generalized Multiview Analysis: A discriminative latent space Hit paper breakdown → | 2012 | 541 |
| 3 | Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies Hit paper breakdown → | 2013 | 526 |
| 4 | Domain Adaptation for Statistical Classifiers Hit paper breakdown → | 2006 | 518 |
| 5 | A Co-training Approach for Multi-view Spectral Clustering Hit paper breakdown → | 2011 | 485 |
| 6 | Deep Unordered Composition Rivals Syntactic Methods for Text Classification Hit paper breakdown → | 2015 | 452 |
| 7 | 2012 | 254 | |
| 8 | 2009 | 236 | |
| 9 | Corpus-Guided Sentence Generation of Natural Images | 2011 | 221 |
| 10 | 2012 | 185 | |
| 11 | 2014 | 179 | |
| 12 | 2006 | 174 | |
| 13 | Incorporating Lexical Priors into Topic Models | 2010 | 155 |
| 14 | 2018 | 142 | |
| 15 | Frustratingly Easy Semi-Supervised Domain Adaptation | 2010 | 108 |
| 16 | Co-regularization Based Semi-supervised Domain Adaptation | 2010 | 99 |
| 17 | 2012 | 94 | |
| 18 | 2005 | 91 | |
| 19 | 2018 | 90 | |
| 20 | Domain Adaptation for Machine Translation by Mining Unseen Words | 2011 | 89 |
About Hal Daumé
Hal Daumé is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Molecular Biology and Safety Research, having authored 179 papers that have together received 8.4k indexed citations. Recurring topics across this work include Topic Modeling (84 papers), Natural Language Processing Techniques (65 papers), Multimodal Machine Learning Applications (18 papers), Machine Learning and Algorithms (18 papers), Domain Adaptation and Few-Shot Learning (16 papers), Machine Learning and Data Classification (13 papers), Advanced Image and Video Retrieval Techniques (12 papers) and Advanced Text Analysis Techniques (11 papers). The work is most often cited by research in Artificial Intelligence (5.9k citations), Computer Vision and Pattern Recognition (3.2k citations), Computational Mathematics (52 citations), Computer Science Applications (256 citations) and Media Technology (354 citations). Hal Daumé has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Abhishek Kumar, Daniel Marcu, Piyush Rai, Jordan Boyd‐Graber, Mohit Iyyer, Lucy Vanderwende, Katrin Kirchhoff, Anurag Kumar, Abhishek Sharma and Amit Goyal. Their work appears in journals such as PLoS ONE, International Journal of Computer Vision, Proceedings of the ACM on Human-Computer Interaction, Computational Linguistics and Machine Learning.
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.