Tom Mitchell

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引用	124290	45520
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i10 指数	312	184

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Sebastian ThrunProfessor of Computer Science, Stanford在 stanford.edu 的电子邮件经过验证
Partha TalukdarGoogle Research and IISc Bangalore在 iisc.ac.in 的电子邮件经过验证
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts Amherst在 cs.umass.edu 的电子邮件经过验证
Marcel JustProfessor of Psychology, Carnegie Mellon University在 cmu.edu 的电子邮件经过验证
Estevam HruschkaMegagon Labs在 megagon.ai 的电子邮件经过验证
Kamal NigamGoogle在 kamalnigam.com 的电子邮件经过验证
Dayne FreitagProgram Director, SRI International在 ai.sri.com 的电子邮件经过验证
Andy CarlsonCarnegie Mellon在 cs.cmu.edu 的电子邮件经过验证
Justin BetteridgePhD Student, Carnegie Mellon University在 cs.cmu.edu 的电子邮件经过验证
Emmanouil Antonios PlataniosResearch Scientist, Scaled Cognition在 scaledcognition.com 的电子邮件经过验证
Brian R. MurphyProfessor of Fisheries Science, Virginia Tech在 vt.edu 的电子邮件经过验证
Amos AzariaComputer Science Dpt. Ariel University, Israel在 ariel.ac.il 的电子邮件经过验证
Francisco PereiraMachine Learning Core, National Institute of Mental Health在 nih.gov 的电子邮件经过验证
Bruce BuchananUniversity Professor of Computer Science (Emeritus), University of Pittsburgh在 cs.pitt.edu 的电子邮件经过验证
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC Berkeley在 cs.berkeley.edu 的电子邮件经过验证
Alona FysheAssociate Professor, Dept. of Computing Science & Dept. of Psychology, University of Alberta在 ualberta.ca 的电子邮件经过验证
Rich CaruanaMicrosoft Research在 microsoft.com 的电子邮件经过验证
Erik BrynjolfssonProfessor at Stanford; NBER; Stanford Digital Economy Lab在 stanford.edu 的电子邮件经过验证
Rebecca HutchinsonOregon State University在 eecs.orst.edu 的电子邮件经过验证
Leila WehbeCarnegie Mellon University在 cmu.edu 的电子邮件经过验证

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Tom Mitchell

Founders University Professor of Machine Learning, Carnegie Mellon University

在 cs.cmu.edu 的电子邮件经过验证 - 首页

Machine Learning cognitive neuroscience natural language understanding


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Machine learning TM Mitchell, TM Mitchell McGraw-hill 1 (9), 1997	39900	1997
Machine learning: Trends, perspectives, and prospects MI Jordan, TM Mitchell Science 349 (6245), 255-260, 2015	10221	2015
Combining labeled and unlabeled data with co-training A Blum, T Mitchell Proceedings of the eleventh annual conference on Computational learning …, 1998	7770	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39, 103-134, 2000	4356	2000
Machine learning: An artificial intelligence approach RS Michalski Springer Science & Business Media, 2013	3856*	2013
Global analysis of protein activities using proteome chips H Zhu, M Bilgin, R Bangham, D Hall, A Casamayor, P Bertone, N Lan, ... science 293 (5537), 2101-2105, 2001	3034	2001
Toward an architecture for never-ending language learning A Carlson, J Betteridge, B Kisiel, B Settles, E Hruschka, T Mitchell Proceedings of the AAAI conference on artificial intelligence 24 (1), 1306-1313, 2010	2572	2010
Explanation-based generalization: A unifying view TM Mitchell, RM Keller, ST Kedar-Cabelli Machine learning 1, 47-80, 1986	2505	1986
Generalization as search TM Mitchell Artificial intelligence 18 (2), 203-226, 1982	2407	1982
Machine learning: a guide to current research, vol. 12 TM Mitchell, JG Carbonell, RS Michalski Springer Science & Business Media, 1986	2025*	1986
Machine learning classifiers and fMRI: a tutorial overview F Pereira, T Mitchell, M Botvinick Neuroimage 45 (1), S199-S209, 2009	2000	2009
Predicting human brain activity associated with the meanings of nouns TM Mitchell, SV Shinkareva, A Carlson, KM Chang, VL Malave, RA Mason, ... science 320 (5880), 1191-1195, 2008	1477	2008
What can machine learning do? Workforce implications E Brynjolfsson, T Mitchell Science 358 (6370), 1530-1534, 2017	1386	2017
Never-Ending Learning AAAI Conference on Artificial Intelligence, 2015	1360*	2015
Webwatcher: A tour guide for the world wide web T Joachims, D Freitag, T Mitchell IJCAI (1), 770-777, 1997	1332	1997
Zero-shot learning with semantic output codes M Palatucci, D Pomerleau, GE Hinton, TM Mitchell Advances in neural information processing systems 22, 2009	1326	2009
The need for biases in learning generalizations TM Mitchell Department of Computer Science, Laboratory for Computer Science Research …, 1980	1283	1980
Learning to extract symbolic knowledge from the World Wide Web M Craven, D DiPasquo, D Freitag, A McCallum, T Mitchell, K Nigam, ... AAAI/IAAI 3 (3.6), 2, 1998	1090	1998
An overview of machine learning JG Carbonell, RS Michalski, TM Mitchell Machine learning, 3-23, 1983	1035	1983
The discipline of machine learning TM Mitchell Carnegie Mellon University, School of Computer Science, Machine Learning …, 2006	1033	2006

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