Thomas Finley
- Artificial Intelligence top 0.2%
- Machine Learning and Algorithms 2
- Topic Modeling 2
- Logic, programming, and type systems 2
- Algorithms and Data Compression 2
- Signal Processing top 1%
- Health Information Management top 0.5%
- Environmental Engineering top 2%
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- Teaching and Learning Programming 4
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- semigroups and automata theory 2
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- DNA and Biological Computing 2
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- Data Mining Algorithms and Applications 2
- Journals
- Machine Learning (1 paper)Annals of Surgery (1 paper)HAL (Le Centre pour la Communication Scientifique Directe) (1 paper)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Thomas Finley
17 papers receiving 7.7k citations
Hit Papers
Peers
Comparison fields: 5 of 218
- Artificial Intelligence 2.8k
- Computer Vision and Pattern Recognition 1.1k
- Signal Processing 506
- Health Information Management 215
- Environmental Engineering 609
Countries citing papers authored by Thomas Finley
This map shows the geographic impact of Thomas Finley'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 Thomas Finley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas Finley more than expected).
Fields of papers citing papers by Thomas Finley
This network shows the impact of papers produced by Thomas Finley. 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 Thomas Finley. The network helps show where Thomas Finley may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Thomas Finley, 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 | Light Gradient Boosting Machine [R package lightgbm version 3.2.0] | 2021 | 1 |
| 2 | LightGBM: A Highly Efficient Gradient Boosting Decision Treebreakdown → | 2017 | 6473 |
| 3 | 2015 | 22 | |
| 4 | 2009 | 10 | |
| 5 | Cutting-plane training of structural SVMsbreakdown → | 2009 | 607 |
| 6 | Supervised k-Means Clustering | 2008 | 15 |
| 7 | 2008 | 154 | |
| 8 | A support vector method for optimizing average precisionbreakdown → | 2007 | 457 |
| 9 | 2006 | 28 | |
| 10 | 2006 | 5 | |
| 11 | 2005 | 132 | |
| 12 | 2004 | 18 | |
| 13 | 2004 | 18 | |
| 14 | 2003 | 1 | |
| 15 | 2003 | 45 | |
| 16 | 2003 | 4 | |
| 17 | 1960 | 8 |
About Thomas Finley
Thomas Finley is a scholar working on Computer Science Applications, Artificial Intelligence, Software, Visual Arts and Performing Arts and Human-Computer Interaction, having authored 17 papers that have together received 8.0k indexed citations. Recurring topics across this work include Teaching and Learning Programming (4 papers), semigroups and automata theory (2 papers), Machine Learning and Algorithms (2 papers), DNA and Biological Computing (2 papers), Topic Modeling (2 papers), Logic, programming, and type systems (2 papers), Data Mining Algorithms and Applications (2 papers) and Algorithms and Data Compression (2 papers). The work is most often cited by research in Artificial Intelligence (2.8k citations), Computer Vision and Pattern Recognition (1.1k citations), Signal Processing (506 citations), Health Information Management (215 citations) and Environmental Engineering (609 citations). Thomas Finley has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Guolin Ke, Tie‐Yan Liu, Wei Chen, Taifeng Wang, Qiwei Ye, Qi Meng, Weidong Ma, Thorsten Joachims, Chun-Nam Yu and Yisong Yue. Their work appears in journals such as Machine Learning, Annals of Surgery, HAL (Le Centre pour la Communication Scientifique Directe), ACM SIGCSE Bulletin and eCommons (Cornell University).
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.