Tom M. Mitchell
Impact in
- Artificial Intelligence top 0.01%
- Machine Learning and Algorithms
- Topic Modeling
- AI-based Problem Solving and Planning
- Natural Language Processing Techniques
- Text and Document Classification Technologies
- Domain Adaptation and Few-Shot Learning
- Advanced Graph Neural Networks
- Computational Mathematics top 0.5%
Papers in
-
- AI-based Problem Solving and Planning 54
- Topic Modeling 48
- Machine Learning and Algorithms 43
- Natural Language Processing Techniques 37
- Reinforcement Learning in Robotics 15
-
- Neurobiology of Language and Bilingualism 23
- Functional Brain Connectivity Studies 18
- Co-authors
- Michael I. Jordan (1 shared paper)Avrim L. Blum (2 shared papers)Sebastian Thrun (9 shared papers)Kamal Nigam (5 shared papers)Smadar T. Kedar-Cabelli (4 shared papers)Richard M. Keller (3 shared papers)Andrew Kachites McCallum (2 shared papers)Erik Brynjolfsson (3 shared papers)
- Journals
- Machine Learning (8 papers)NeuroImage (6 papers)AI Magazine (5 papers)PLoS ONE (4 papers)Science (4 papers)
- Partner nations
- United StatesIndiaIsrael
In The Last Decade
Tom M. Mitchell
267 papers receiving 33.4k citations
Tom M. Mitchell's Hit Papers
Peers
Comparison fields: 5 of 233
- Artificial Intelligence 18.1k
- Computational Mathematics 162
- Health Informatics 459
- Cognitive Neuroscience 3.4k
- Information Systems 4.1k
Countries citing papers authored by Tom M. Mitchell
This map shows the geographic impact of Tom M. Mitchell'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 Tom M. Mitchell with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom M. Mitchell more than expected).
Fields of papers citing papers by Tom M. Mitchell
This network shows the impact of papers produced by Tom M. Mitchell. 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 Tom M. Mitchell. The network helps show where Tom M. Mitchell may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom M. Mitchell, 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 283 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Machine learning: Trends, perspectives, and prospects Hit paper breakdown → | 2015 | 7261 |
| 2 | Combining labeled and unlabeled data with co-training Hit paper breakdown → | 1998 | 4284 |
| 3 | Text Classification from Labeled and Unlabeled Documents using EM Hit paper breakdown → | 2000 | 2187 |
| 4 | Toward an Architecture for Never-Ending Language Learning Hit paper breakdown → | 2010 | 1441 |
| 5 | Machine learning classifiers and fMRI: A tutorial overview Hit paper breakdown → | 2008 | 1336 |
| 6 | Generalization as search Hit paper breakdown → | 1982 | 1100 |
| 7 | Explanation-Based Generalization: A Unifying View Hit paper breakdown → | 1986 | 948 |
| 8 | Predicting Human Brain Activity Associated with the Meanings of Nouns Hit paper breakdown → | 2008 | 876 |
| 9 | What can machine learning do? Workforce implications Hit paper breakdown → | 2017 | 715 |
| 10 | 1986 | 585 | |
| 11 | 2004 | 531 | |
| 12 | 1999 | 521 | |
| 13 | Web Watcher: A Tour Guide for the World Wide Web. Hit paper breakdown → | 1997 | 511 |
| 14 | Learning to extract symbolic knowledge from the World Wide Web Hit paper breakdown → | 1998 | 510 |
| 15 | Never-ending learning Hit paper breakdown → | 2018 | 376 |
| 16 | 2000 | 357 | |
| 17 | Zero-Shot Learning with Semantic Output Codes Hit paper breakdown → | 2018 | 357 |
| 18 | What Can Machines Learn and What Does It Mean for Occupations and the Economy? Hit paper breakdown → | 2018 | 341 |
| 19 | 1995 | 335 | |
| 20 | Coupled semi-supervised learning for information extraction Hit paper breakdown → | 2010 | 319 |
About Tom M. Mitchell
Tom M. Mitchell is a scholar working on Artificial Intelligence, Cognitive Neuroscience, Information Systems, Human-Computer Interaction and Developmental and Educational Psychology, having authored 283 papers that have together received 35.8k indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (54 papers), Topic Modeling (48 papers), Machine Learning and Algorithms (43 papers), Natural Language Processing Techniques (37 papers), Neurobiology of Language and Bilingualism (23 papers), Functional Brain Connectivity Studies (18 papers), Reinforcement Learning in Robotics (15 papers) and Web Data Mining and Analysis (13 papers). The work is most often cited by research in Artificial Intelligence (18.1k citations), Computational Mathematics (162 citations), Health Informatics (459 citations), Cognitive Neuroscience (3.4k citations) and Information Systems (4.1k citations). Tom M. Mitchell has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Michael I. Jordan, Avrim L. Blum, Sebastian Thrun, Kamal Nigam, Smadar T. Kedar-Cabelli, Richard M. Keller, Andrew Kachites McCallum, Erik Brynjolfsson, Francisco Pereira and Matthew Botvinick. Their work appears in journals such as Machine Learning, NeuroImage, AI Magazine, PLoS ONE and Science.
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.