Lester Mackey
Impact in
- Statistics and Probability top 5%
- Statistical Methods and Inference
Papers in
-
- Machine Learning and Algorithms 6
- Bayesian Methods and Mixture Models 5
- Computational Physics and Python Applications 4
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- Markov Chains and Monte Carlo Methods 6
- Statistical Methods and Inference 5
- Random Matrices and Applications 5
- Co-authors
- Michael I. Jordan (6 shared papers)Ameet Talwalkar (3 shared papers)John C. Duchi (2 shared papers)Rina Foygel (1 shared paper)Emil Stefanov (1 shared paper)Dawn Song (1 shared paper)Elaine Shi (1 shared paper)Ling Huang (1 shared paper)
- Journals
- ACM SIGPLAN Notices (2 papers)Journal of the Royal Statistical Society Series B (Statistical Methodology) (2 papers)The Annals of Probability (1 paper)Journal of the American Medical Informatics Association (1 paper)PLoS ONE (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Lester Mackey
48 papers receiving 872 citations
Peers
Comparison fields: 5 of 137
- Statistics and Probability 96
- Computational Mathematics 7
- Occupational Therapy 41
- Artificial Intelligence 304
- Statistical and Nonlinear Physics 100
Countries citing papers authored by Lester Mackey
This map shows the geographic impact of Lester Mackey'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 Lester Mackey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lester Mackey more than expected).
Fields of papers citing papers by Lester Mackey
This network shows the impact of papers produced by Lester Mackey. 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 Lester Mackey. The network helps show where Lester Mackey may publish in the future.
Co-authors
The 25 scholars most cited alongside Lester Mackey, 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 54 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 138 | |
| 2 | Deflation Methods for Sparse PCA | 2008 | 109 |
| 3 | 2006 | 79 | |
| 4 | 2018 | 72 | |
| 5 | On the Consistency of Ranking Algorithms | 2010 | 51 |
| 6 | 2016 | 44 | |
| 7 | 1 Corrupted Sensing: Novel Guarantees for Separating Structured Signals | 2016 | 37 |
| 8 | 2017 | 31 | |
| 9 | 2013 | 28 | |
| 10 | 2014 | 27 | |
| 11 | 2007 | 25 | |
| 12 | 2023 | 22 | |
| 13 | 2006 | 21 | |
| 14 | 2018 | 18 | |
| 15 | 2022 | 17 | |
| 16 | 2018 | 15 | |
| 17 | 2016 | 15 | |
| 18 | 2022 | 15 | |
| 19 | 2025 | 13 | |
| 20 | Divide-and-Conquer Matrix Factorization | 2011 | 13 |
About Lester Mackey
Lester Mackey is a scholar working on Artificial Intelligence, Statistics and Probability, Computational Mechanics, Computer Vision and Pattern Recognition and Nuclear and High Energy Physics, having authored 54 papers that have together received 910 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (7 papers), Markov Chains and Monte Carlo Methods (6 papers), Machine Learning and Algorithms (6 papers), Statistical Methods and Inference (5 papers), Bayesian Methods and Mixture Models (5 papers), Random Matrices and Applications (5 papers), Particle physics theoretical and experimental studies (5 papers) and Computational Physics and Python Applications (4 papers). The work is most often cited by research in Statistics and Probability (96 citations), Computational Mathematics (7 citations), Occupational Therapy (41 citations), Artificial Intelligence (304 citations) and Statistical and Nonlinear Physics (100 citations). Lester Mackey has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Michael I. Jordan, Ameet Talwalkar, John C. Duchi, Rina Foygel, Emil Stefanov, Dawn Song, Elaine Shi, Ling Huang, Eui Chul Richard Shin and Neil Zhenqiang Gong. Their work appears in journals such as ACM SIGPLAN Notices, Journal of the Royal Statistical Society Series B (Statistical Methodology), The Annals of Probability, Journal of the American Medical Informatics Association and PLoS ONE.
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.