Pedro Domingos

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Matthew RichardsonMicrosoft ResearchAdresse e-mail validée de microsoft.com
Geoff HultenGoogleAdresse e-mail validée de google.com
Hoifung PoonGeneral Manager, Microsoft Health FuturesAdresse e-mail validée de microsoft.com
Daniel LowdAssociate Professor of Computer Science, University of OregonAdresse e-mail validée de cs.uoregon.edu
Parag SinglaIndian Institute of Technology DelhiAdresse e-mail validée de cse.iitd.ac.in
Alon HalevyGoogleAdresse e-mail validée de google.com
AnHai DoanProfessor of Computer Science, University of Wisconsin-MadisonAdresse e-mail validée de cs.wisc.edu
Daniel WeldAllen Institute for AI & University of WashingtonAdresse e-mail validée de cs.washington.edu
Stanley KokNational University of SingaporeAdresse e-mail validée de nus.edu.sg
Michael J. PazzaniDistinguished Principal ScientistAdresse e-mail validée de isi.edu
Aniruddh NathGoogle, LLCAdresse e-mail validée de google.com
Robert GensAdresse e-mail validée de cs.washington.edu
Vibhav GogateThe University of Texas at DallasAdresse e-mail validée de utdallas.edu
MausamProfessor of Computer Science & Engineering, Indian Institute of Technology DelhiAdresse e-mail validée de cs.washington.edu
Thomas DietterichDistinguished Professor (Emeritus), Computer Science, Oregon State UniversityAdresse e-mail validée de cs.orst.edu
Abram (Abe) FriesenSenior Research Scientist, DeepMindAdresse e-mail validée de cs.washington.edu
Steven WolfmanUniversity of British ColumbiaAdresse e-mail validée de cs.ubc.ca
Rakesh AgrawalData Insights LaboratoriesAdresse e-mail validée de datainsightslabs.com
Lise GetoorDistinguished Professor of Computer Science & Engineering, University of California, Santa CruzAdresse e-mail validée de ucsc.edu
Jesse DavisProfessor, Department of Computer Science, KU LeuvenAdresse e-mail validée de cs.kuleuven.be

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Pedro Domingos

Professor of Computer Science and Engineering, University of Washington

Adresse e-mail validée de cs.washington.edu - Page d'accueil

Machine Learning Artificial Intelligence Data Science


Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
On the optimality of the simple Bayesian classifier under zero-one loss P Domingos, M Pazzani Machine learning 29 (2), 103-130, 1997	4732	1997
A few useful things to know about machine learning P Domingos Communications of the ACM 55 (10), 78-87, 2012	4606	2012
Markov logic networks M Richardson, P Domingos Machine learning 62, 107-136, 2006	3848	2006
Mining the network value of customers P Domingos, M Richardson Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001	3702	2001
Mining high-speed data streams P Domingos, G Hulten Proceedings of the sixth ACM SIGKDD international conference on Knowledge …, 2000	3178	2000
Mining time-changing data streams G Hulten, L Spencer, P Domingos Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001	2495	2001
Mining knowledge-sharing sites for viral marketing M Richardson, P Domingos Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002	2265	2002
The master algorithm: How the quest for the ultimate learning machine will remake our world P Domingos Basic Books, 2015	2231	2015
Metacost: A general method for making classifiers cost-sensitive P Domingos Proceedings of the fifth ACM SIGKDD international conference on Knowledge …, 1999	2179	1999
Learning to map between ontologies on the semantic web AH Doan, J Madhavan, P Domingos, A Halevy Proceedings of the 11th international conference on World Wide Web, 662-673, 2002	1494	2002
Trust management for the semantic web M Richardson, R Agrawal, P Domingos International semantic Web conference, 351-368, 2003	1362	2003
Adversarial classification N Dalvi, P Domingos, Mausam, S Sanghai, D Verma Proceedings of the tenth ACM SIGKDD international conference on Knowledge …, 2004	1359	2004
Beyond independence: Conditions for the optimality of the simple bayesian classifier P Domingos, M Pazzani Proc. 13th Intl. Conf. Machine Learning, 105-112, 1996	1240	1996
Reconciling schemas of disparate data sources: A machine-learning approach AH Doan, P Domingos, AY Halevy Proceedings of the 2001 ACM SIGMOD international conference on Management of …, 2001	1189	2001
Sum-product networks: A new deep architecture H Poon, P Domingos Proceedings of the Twenty-Seventh Conference on Uncertainty in Artificial …, 2011	929	2011
Ontology matching: A machine learning approach AH Doan, J Madhavan, P Domingos, A Halevy Handbook on ontologies, 385-403, 2004	771	2004
Markov Logic P Domingos, D Lowd Markov Logic: An Interface Layer for Artificial Intelligence, 9-22, 2009	721	2009
Tree induction for probability-based ranking F Provost, P Domingos Machine learning 52, 199-215, 2003	714	2003
Learning to match ontologies on the semantic web AH Doan, J Madhavan, R Dhamankar, P Domingos, A Halevy The VLDB journal 12, 303-319, 2003	701	2003
The role of Occam's razor in knowledge discovery P Domingos Data mining and knowledge discovery 3, 409-425, 1999	699	1999

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