John Lafferty
- Artificial Intelligence top 0.01%
- Topic Modeling 26
- Natural Language Processing Techniques 23
- Bayesian Modeling and Causal Inference 20
- Bayesian Methods and Mixture Models 19
- Machine Learning and Algorithms 14
- Algorithms and Data Compression 13
- Information Systems top 0.02%
- Signal Processing top 0.2%
- General Social Sciences top 0.01%
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- Statistical Methods and Inference 25
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- Hemoglobinopathies and Related Disorders 18
- Co-authors
- Andrew McCallumFernando C. N. PereiraChengXiang ZhaiDavid M. BleiXiaojin ZhuZoubin GhahramaniAdam BergerS. Della Pietra
- Journals
- American Journal of Clinical Pathology (8 papers)ACM SIGIR Forum (5 papers)Transactions of the American Mathematical Society (4 papers)
- Partner nations
- United StatesCanadaUnited Kingdom
In The Last Decade
John Lafferty
173 papers receiving 23.9k citations
Hit Papers
Peers
Comparison fields: 5 of 218
- Artificial Intelligence 17.5k
- Computer Vision and Pattern Recognition 5.9k
- Information Systems 5.3k
- Signal Processing 2.1k
- General Social Sciences 627
Countries citing papers authored by John Lafferty
This map shows the geographic impact of John Lafferty'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 John Lafferty with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John Lafferty more than expected).
Fields of papers citing papers by John Lafferty
This network shows the impact of papers produced by John Lafferty. 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 John Lafferty. The network helps show where John Lafferty may publish in the future.
Co-authorship network
The 25 scholars most cited alongside John Lafferty, 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 | 2024 | 4 | |
| 2 | 2022 | 15 | |
| 3 | Surfing: Iterative Optimization Over Incrementally Trained Deep Networks | 2019 | 3 |
| 4 | Prediction Rule Reshaping | 2018 | 0 |
| 5 | Computation-Risk Tradeoffs for Covariance-Thresholded Regression | 2013 | 5 |
| 6 | The Bigraphical Lasso | 2013 | 3 |
| 7 | Sequential Nonparametric Regression | 2012 | 2 |
| 8 | Exponential Concentration for Mutual Information Estimation with Application to Forests | 2012 | 11 |
| 9 | SpAM: Sparse Additive Models | 2007 | 89 |
| 10 | Prediction and discovery : AMS-IMS-SIAM Joint Summer Research Conference, Machine and Statistical Learning: Prediction and Discovery, June 25-29, 2006, Snowbird, Utah | 2007 | 4 |
| 11 | Rodeo: Sparse Nonparametric Regression in High Dimensions | 2005 | 10 |
| 12 | Correlated Topic Modelsbreakdown → | 2005 | 611 |
| 13 | Information Diffusion Kernels | 2002 | 33 |
| 14 | Diffusion Kernels on Graphs and Other Discrete Input Spacesbreakdown → | 2002 | 462 |
| 15 | 1997 | 10 | |
| 16 | 1997 | 54 | |
| 17 | 1992 | 7 | |
| 18 | 1992 | 10 | |
| 19 | A statistical approach to machine translationbreakdown → | 1990 | 1013 |
| 20 | 1988 | 5 |
About John Lafferty
John Lafferty is a scholar working on Statistics and Probability, Artificial Intelligence and Genetics, having authored 178 papers that have together received 26.1k indexed citations. Recurring topics across this work include Topic Modeling (26 papers), Statistical Methods and Inference (25 papers), Natural Language Processing Techniques (23 papers), Bayesian Modeling and Causal Inference (20 papers), Bayesian Methods and Mixture Models (19 papers), Hemoglobinopathies and Related Disorders (18 papers), Machine Learning and Algorithms (14 papers) and Algorithms and Data Compression (13 papers). The work is most often cited by research in Artificial Intelligence (17.5k citations), Computer Vision and Pattern Recognition (5.9k citations) and Information Systems (5.3k citations). John Lafferty has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Andrew McCallum, Fernando C. N. Pereira, ChengXiang Zhai, David M. Blei, Xiaojin Zhu, Zoubin Ghahramani, Adam Berger, S. Della Pietra, V. Della Pietra and Risi Kondor. Their work appears in journals such as American Journal of Clinical Pathology, ACM SIGIR Forum, Transactions of the American Mathematical Society, Journal of Machine Learning Research and Archives of Pathology & Laboratory Medicine.
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.