Tom M. Mitchell

48.7k total citations · 12 hit papers
204 papers, 27.9k citations indexed

About

Tom M. Mitchell is a scholar working on Artificial Intelligence, Cognitive Neuroscience and Information Systems. According to data from OpenAlex, Tom M. Mitchell has authored 204 papers receiving a total of 27.9k indexed citations (citations by other indexed papers that have themselves been cited), including 128 papers in Artificial Intelligence, 34 papers in Cognitive Neuroscience and 24 papers in Information Systems. Recurrent topics in Tom M. Mitchell's work include Topic Modeling (60 papers), Natural Language Processing Techniques (49 papers) and Machine Learning and Algorithms (26 papers). Tom M. Mitchell is often cited by papers focused on Topic Modeling (60 papers), Natural Language Processing Techniques (49 papers) and Machine Learning and Algorithms (26 papers). Tom M. Mitchell collaborates with scholars based in United States, United Kingdom and India. Tom M. Mitchell's co-authors include Michael I. Jordan, Avrim Blum, Sebastian Thrun, Kamal Nigam, Andrew Kachites McCallum, Erik Brynjolfsson, Francisco Pereira, Matthew Botvinick, J. Andrew Carlson and Smadar T. Kedar-Cabelli and has published in prestigious journals such as Nature, Science and Bioinformatics.

In The Last Decade

Tom M. Mitchell

198 papers receiving 25.9k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Machine learning: Trends, perspectives, and prospects

2015 6.0k citations Tom M. Mitchell et al. profile →
Combining labeled and unlabeled data with co-training

1998 3.6k citations Tom M. Mitchell et al. profile →
Text Classification from Labeled and Unlabeled Documents using EM

2000 1.9k citations Kamal Nigam, Sebastian Thrun et al. profile →
Global Analysis of Protein Activities Using Proteome Chips

2001 1.5k citations Tom M. Mitchell et al. profile →
Machine learning classifiers and fMRI: A tutorial overview

2008 1.2k citations Tom M. Mitchell et al. NeuroImage profile →
Toward an Architecture for Never-Ending Language Learning

2010 1.2k citations Justin Betteridge, Bryan Kisiel et al. profile →
Predicting Human Brain Activity Associated with the Meanings of Nouns

2008 805 citations Tom M. Mitchell et al. profile →
Generalization as search

1982 803 citations Tom M. Mitchell profile →
Explanation-Based Generalization: A Unifying View

1986 663 citations Tom M. Mitchell, Smadar T. Kedar-Cabelli et al. profile →
What can machine learning do? Workforce implications

2017 592 citations Tom M. Mitchell et al. profile →
What Can Machines Learn and What Does It Mean for Occupations and the Economy?

2018 298 citations Tom M. Mitchell et al. profile →
Zero-Shot Learning with Semantic Output Codes

2018 291 citations Tom M. Mitchell et al. Figshare profile →

Peers

Countries citing papers authored by Tom M. Mitchell

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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-authorship network of co-authors of Tom M. Mitchell

This figure shows the co-authorship network connecting the top 25 collaborators of Tom M. Mitchell. A scholar is included among the top collaborators of Tom M. Mitchell based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tom M. Mitchell. Tom M. Mitchell is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Interactive Task Learning from GUI-Grounded Natural Language Instructions and Demonstrations 2020 ·Toby Jia-Jun Li, Tom M. Mitchell, Brad A. Myers	10
2	Interactive Task and Concept Learning from Natural Language Instructions and GUI Demonstrations 2019 ·arXiv (Cornell University) ·Toby Jia-Jun Li, (unknown), (unknown), (unknown), Tom M. Mitchell, Brad A. Myers	1
3	Leimu: Gloveless music interaction using a wrist mounted leap motion 2016 ·New Interfaces for Musical Expression ·(unknown), (unknown), (unknown), (unknown), Tom M. Mitchell	6
4	AskWorld: budget-sensitive query evaluation for knowledge-on-demand 2015 ·International Conference on Artificial Intelligence ·(unknown), Partha Talukdar, Manuela Veloso, Tom M. Mitchell	3
5	Multivariate analysis of correlation between electrophysiological and hemodynamic responses during cognitive processing 2014 ·NeuroImage ·Jan Kujala, Gustavo Sudre, Johanna Vartiainen, Mia Liljeström, Tom M. Mitchell, Riitta Salmelin	18
6	Assuming Facts Are Expressed More Than Once. 2014 ·The Florida AI Research Society ·Justin Betteridge, Alan Ritter, Tom M. Mitchell	1
7	Improving Learning and Inference in a Large Knowledge-Base using Latent Syntactic Cues 2013 ·Figshare ·Matt Gardner, Partha Talukdar, Bryan Kisiel, Tom M. Mitchell	58
8	Discovering Relations between Noun Categories 2011 ·Empirical Methods in Natural Language Processing ·Thahir Mohamed, Estevam Hruschka, Tom M. Mitchell	55
9	Detecting Significant Multidimensional Spatial Clusters 2004 ·Neural Information Processing Systems ·Daniel B. Neill, Andrew Moore, Francisco Pereira, Tom M. Mitchell	37
10	Training fMRI classifiers to discriminate cognitive states across multiple subjects 2003 ·Neural Information Processing Systems ·Xuerui Wang, Rebecca Hutchinson, Tom M. Mitchell	22
11	Training fMRI Classifiers to Detect Cognitive States across Multiple Human Subjects 2003 ·Neural Information Processing Systems ·Xuerui Wang, Rebecca Hutchinson, Tom M. Mitchell	41
12	Discovering Test Set Regularities in Relational Domains 2000 ·International Conference on Machine Learning ·Seán Slattery, Tom M. Mitchell	54
13	Learning to classify text from labeled and unlabeled documents 1998 ·National Conference on Artificial Intelligence ·Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell	220
14	Integrating inductive neural network learning and explanation-based learning 1993 ·International Joint Conference on Artificial Intelligence ·Sebastian Thrun, Tom M. Mitchell	22
15	A comparative analysis of chunking and decision-analytic control 1993 ·MIT Press eBooks ·Oren Etzioni, Tom M. Mitchell	1
16	Explanation-Based Neural Network Learning for Robot Control 1992 ·Neural Information Processing Systems ·Tom M. Mitchell, Sebastian Thrun	59
17	Learning from solution paths: an approach to the credit assignment problem 1989 ·Derek Sleeman, Pat Langley, Tom M. Mitchell	2
18	Machine learning: a guide to current research 1986 ·CERN Bulletin ·Tom M. Mitchell, Jaime Carbonell, Ryszard S. Michalski	71
19	LEAP: a learning apprentice for VLSI design 1985 ·International Joint Conference on Artificial Intelligence ·Tom M. Mitchell, Sridhar Mahadevan, Louis Steinberg	160
20	An intelligent aid for circuit redesign 1983 ·National Conference on Artificial Intelligence ·Tom M. Mitchell, Louis Steinberg, Smadar T. Kedar-Cabelli, (unknown), (unknown), (unknown)	27

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.

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