Charles Sutton

Cited by

	All	Since 2016
Citations	10133	5583
h-index	41	31
i10-index	73	60

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Co-authors

Andrew McCallumDistinguished Professor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Miltiadis AllamanisMicrosoft ResearchVerified email at allamanis.com
Earl T. BarrProfessor, University College LondonVerified email at ucl.ac.uk
Akash SrivastavaMIT, IBM Research, University of EdinburghVerified email at mit.edu
Michael I. JordanProfessor of Electrical Engineering and Computer Sciences and Professor of Statistics, UC BerkeleyVerified email at cs.berkeley.edu
Christian BirdMicrosoft ResearchVerified email at microsoft.com
Peter BodikPrincipal Researcher at Microsoft ResearchVerified email at microsoft.com
David PattersonProfessor of Computer Science, UC BerkeleyVerified email at cs.berkeley.edu
Armando FoxUC BerkeleyVerified email at berkeley.edu
Nigel GoddardAssociate Professor, Informatics, University of EdinburghVerified email at ed.ac.uk
Lazar ValkovUniversity of EdinburghVerified email at sms.ed.ac.uk
Mingjun ZhongDepartment of Computing Science, University of Aberdeen, UKVerified email at abdn.ac.uk
Andrew D GordonMicrosoft Research and University of EdinburghVerified email at microsoft.com
Yanlei DiaoProfessor of Computer Science, University of Massachusetts AmherstVerified email at cs.umass.edu
Jaroslav FowkesUniversity of OxfordVerified email at maths.ox.ac.uk
Benjamin I. P. RubinsteinProfessor, School of Computing and Information Systems, The University of MelbourneVerified email at unimelb.edu.au
Anthony D. JosephUniversity of California BerkeleyVerified email at eecs.berkeley.edu
Prem DevanbuProfessor (பேராசிரியர்), University of California, Davis.Verified email at ucdavis.edu
Michael U. GutmannUniversity of EdinburghVerified email at ed.ac.uk
Paul R. CohenSchool of Computing and Information University of PittsburghVerified email at pitt.edu

Charles Sutton

Google, University of Edinburgh

Verified email at inf.ed.ac.uk - Homepage

Machine learning artificial intelligence natural language processing programming languages software engineering


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
An introduction to conditional random fields for relational learning C Sutton, A McCallum Introduction to statistical relational learning 2, 93-128, 2006	2227	2006
Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007	1717	2007
Dynamic conditional random fields: Factorized probabilistic models for labeling and segmenting sequence data. C Sutton, A McCallum, K Rohanimanesh Journal of Machine Learning Research 8 (3), 2007	583	2007
A survey of machine learning for big code and naturalness M Allamanis, ET Barr, P Devanbu, C Sutton ACM Computing Surveys (CSUR) 51 (4), 1-37, 2018	313	2018
Veegan: Reducing mode collapse in gans using implicit variational learning A Srivastava, L Valkov, C Russell, MU Gutmann, C Sutton arXiv preprint arXiv:1705.07761, 2017	281	2017
Learning natural coding conventions M Allamanis, ET Barr, C Bird, C Sutton Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations …, 2014	281	2014
A convolutional attention network for extreme summarization of source code M Allamanis, H Peng, C Sutton International conference on machine learning, 2091-2100, 2016	277	2016
Statistical Machine Learning Makes Automatic Control Practical for Internet Datacenters. P Bodík, R Griffith, CA Sutton, A Fox, MI Jordan, DA Patterson HotCloud 9, 12-12, 2009	269	2009
Suggesting accurate method and class names M Allamanis, ET Barr, C Bird, C Sutton Proceedings of the 2015 10th Joint Meeting on Foundations of Software …, 2015	262	2015
Mining source code repositories at massive scale using language modeling M Allamanis, C Sutton 2013 10th Working Conference on Mining Software Repositories (MSR), 207-216, 2013	243	2013
Exploiting Machine Learning to Subvert Your Spam Filter. B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ... LEET 8, 1-9, 2008	240	2008
Piecewise training for undirected models C Sutton, A McCallum arXiv preprint arXiv:1207.1409, 2012	222	2012
Autoencoding variational inference for topic models A Srivastava, C Sutton arXiv preprint arXiv:1703.01488, 2017	183	2017
Collective segmentation and labeling of distant entities in information extraction C Sutton, A McCallum MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2004	166	2004
Probabilistic inference over RFID streams in mobile environments T Tran, C Sutton, R Cocci, Y Nie, Y Diao, P Shenoy 2009 IEEE 25th International Conference on Data Engineering, 1096-1107, 2009	154	2009
Sequence-to-point learning with neural networks for non-intrusive load monitoring C Zhang, M Zhong, Z Wang, N Goddard, C Sutton Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	136	2018
Mining idioms from source code M Allamanis, C Sutton Proceedings of the 22nd acm sigsoft international symposium on foundations …, 2014	136	2014
Piecewise pseudolikelihood for efficient training of conditional random fields C Sutton, A McCallum Proceedings of the 24th international conference on Machine learning, 863-870, 2007	130	2007
Why, when, and what: analyzing stack overflow questions by topic, type, and code M Allamanis, C Sutton 2013 10th Working Conference on Mining Software Repositories (MSR), 53-56, 2013	120	2013
Misleading learners: Co-opting your spam filter B Nelson, M Barreno, FJ Chi, AD Joseph, BIP Rubinstein, U Saini, ... Machine learning in cyber trust, 17-51, 2009	93	2009

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