Adam Pocock
Impact in
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- Face and Expression Recognition
- Artificial Intelligence top 5%
- Machine Learning and Data Classification
- Neural Networks and Applications
- Text and Document Classification Technologies
- Evolutionary Algorithms and Applications
Papers in
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- Machine Learning and Data Classification 7
- Bayesian Modeling and Causal Inference 3
- Neural Networks and Applications 3
- Machine Learning and Algorithms 3
- Evolutionary Algorithms and Applications 2
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- Face and Expression Recognition 4
- Co-authors
- Gavin Brown (7 shared papers)Mikel Luján (5 shared papers)Mingjie Zhao (2 shared papers)Mingbo Zhao (1 shared paper)Michael Wick (1 shared paper)Jeremy Singer (1 shared paper)Konstantinos Sechidis (2 shared papers)Laura Azzimonti (2 shared papers)
- Journals
- Journal of Machine Learning Research (3 papers)Machine Learning (2 papers)Electronic Notes in Theoretical Computer Science (1 paper)cIRcle (University of British Columbia) (1 paper)Proceedings of the AAAI Conference on Artificial Intelligence (1 paper)
- Partner nations
- United KingdomUnited StatesCanada
In The Last Decade
Adam Pocock
14 papers receiving 909 citations
Adam Pocock's Hit Papers
Peers
Comparison fields: 5 of 122
- Computer Vision and Pattern Recognition 302
- Artificial Intelligence 459
- Signal Processing 107
- Software 24
- Analytical Chemistry 41
Countries citing papers authored by Adam Pocock
This map shows the geographic impact of Adam Pocock'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 Adam Pocock with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam Pocock more than expected).
Fields of papers citing papers by Adam Pocock
This network shows the impact of papers produced by Adam Pocock. 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 Adam Pocock. The network helps show where Adam Pocock may publish in the future.
Co-authors
The 15 scholars most cited alongside Adam Pocock, 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 | Conditional likelihood maximisation: a unifying framework for information theoretic feature selection Hit paper breakdown → | 2012 | 785 |
| 2 | Beyond Fano's inequality: bounds on the optimal F-score, BER, and cost-sensitive risk and their implications | 2013 | 28 |
| 3 | 2010 | 27 | |
| 4 | 2019 | 23 | |
| 5 | Conditional Likelihood Maximisation: A Unifying Framework for Mutual Information Feature Selection | 2012 | 22 |
| 6 | 2016 | 19 | |
| 7 | Augur: Data-Parallel Probabilistic Modeling | 2014 | 11 |
| 8 | Feature Selection Via Joint Likelihood | 2013 | 9 |
| 9 | 2015 | 5 | |
| 10 | 2023 | 3 | |
| 11 | 2024 | 2 | |
| 12 | 2020 | 2 | |
| 13 | Informative Priors for Markov Blanket Discovery | 2012 | 2 |
| 14 | MSc Project Feature Selection using Information Theoretic Techniques | 2008 | 1 |
| 15 | 2025 | 0 |
About Adam Pocock
Adam Pocock is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems, Information Systems and Management and Conservation, having authored 15 papers that have together received 939 indexed citations. Recurring topics across this work include Machine Learning and Data Classification (7 papers), Face and Expression Recognition (4 papers), Bayesian Modeling and Causal Inference (3 papers), Neural Networks and Applications (3 papers), Scientific Computing and Data Management (3 papers), Machine Learning and Algorithms (3 papers), Research Data Management Practices (2 papers) and Evolutionary Algorithms and Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (302 citations), Artificial Intelligence (459 citations), Signal Processing (107 citations), Software (24 citations) and Analytical Chemistry (41 citations). Adam Pocock has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Gavin Brown, Mikel Luján, Mingjie Zhao, Mingbo Zhao, Michael Wick, Jeremy Singer, Konstantinos Sechidis, Laura Azzimonti, Giorgio Corani and Joseph Tassarotti. Their work appears in journals such as Journal of Machine Learning Research, Machine Learning, Electronic Notes in Theoretical Computer Science, cIRcle (University of British Columbia) and Proceedings of the AAAI Conference on Artificial Intelligence.
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.