Tom Mitchell

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Sebastian ThrunProfessor of Computer Science, StanfordVerificeret mail på stanford.edu
Partha TalukdarGoogle Research and IISc BangaloreVerificeret mail på iisc.ac.in
Marcel JustProfessor of Psychology, Carnegie Mellon UniversityVerificeret mail på cmu.edu
Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerificeret mail på cs.umass.edu
Estevam HruschkaMegagon LabsVerificeret mail på megagon.ai
Dayne FreitagProgram Director, SRI InternationalVerificeret mail på ai.sri.com
Kamal NigamGoogleVerificeret mail på kamalnigam.com
Andy CarlsonCarnegie MellonVerificeret mail på cs.cmu.edu
Justin BetteridgePhD Student, Carnegie Mellon UniversityVerificeret mail på cs.cmu.edu
Brian R. MurphyProfessor of Fisheries Science, Virginia TechVerificeret mail på vt.edu
Emmanouil Antonios PlataniosResearch Scientist, Scaled CognitionVerificeret mail på scaledcognition.com
Francisco PereiraMachine Learning Team, National Institute of Mental HealthVerificeret mail på nih.gov
Bruce BuchananUniversity Professor of Computer Science (Emeritus), University of PittsburghVerificeret mail på cs.pitt.edu
Rich CaruanaMicrosoft ResearchVerificeret mail på microsoft.com
Alona FysheAssociate Professor, Dept. of Computing Science & Dept. of Psychology, University of AlbertaVerificeret mail på ualberta.ca
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerificeret mail på cs.berkeley.edu
Rebecca HutchinsonOregon State UniversityVerificeret mail på eecs.orst.edu
Erik BrynjolfssonProfessor at Stanford; NBER; Stanford Digital Economy LabVerificeret mail på stanford.edu
Avrim BlumProfessor and Chief Academic Officer, Toyota Technological Institute at ChicagoVerificeret mail på ttic.edu
Leila WehbeCarnegie Mellon UniversityVerificeret mail på cmu.edu

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Tom Mitchell

Founders University Professor of Machine Learning, Carnegie Mellon University

Verificeret mail på cs.cmu.edu - Startside

Machine Learning cognitive neuroscience natural language understanding


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
Machine learning: Trends, perspectives, and prospects MI Jordan, TM Mitchell Science 349 (6245), 255-260, 2015	8403	2015
Combining labeled and unlabeled data with co-training A Blum, T Mitchell Proceedings of the eleventh annual conference on Computational learning …, 1998	7578	1998
Text classification from labeled and unlabeled documents using EM K Nigam, AK McCallum, S Thrun, T Mitchell Machine learning 39, 103-134, 2000	4268	2000
Machine learning: An artificial intelligence approach RS Michalski, JG Carbonell, TM Mitchell Springer Science & Business Media, 2013	3746*	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	3001	2001
Explanation-based generalization: A unifying view TM Mitchell, RM Keller, ST Kedar-Cabelli Machine learning 1, 47-80, 1986	2463	1986
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	2448	2010
Generalization as search TM Mitchell Artificial intelligence 18 (2), 203-226, 1982	2360	1982
Machine learning classifiers and fMRI: a tutorial overview F Pereira, T Mitchell, M Botvinick Neuroimage 45 (1), S199-S209, 2009	1924	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	1441	2008
Webwatcher: A tour guide for the world wide web T Joachims, D Freitag, T Mitchell IJCAI (1), 770-777, 1997	1315	1997
Never-Ending Learning AAAI Conference on Artificial Intelligence, 2015	1267*	2015
Zero-shot learning with semantic output codes M Palatucci, D Pomerleau, GE Hinton, TM Mitchell Advances in neural information processing systems 22, 2009	1243	2009
The need for biases in learning generalizations TM Mitchell Department of Computer Science, Laboratory for Computer Science Research …, 1980	1228	1980
What can machine learning do? Workforce implications E Brynjolfsson, T Mitchell Science 358 (6370), 1530-1534, 2017	1169	2017
Machine learning: a guide to current research, vol. 12 TM Mitchell, JG Carbonell, RS Michalski Springer Science & Business Media, 1986	1116*	1986
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	1058	1998
Webwatcher: A learning apprentice for the world wide web R Armstrong, D Freitag, T Joachims, T Mitchell AAAI Spring symposium on Information gathering from Heterogeneous …, 1995	994	1995
The discipline of machine learning TM Mitchell Carnegie Mellon University, School of Computer Science, Machine Learning …, 2006	968	2006
An overview of machine learning JG Carbonell, RS Michalski, TM Mitchell Machine learning, 3-23, 1983	946	1983

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