Charles Sutton
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
22932006
Introduction to statistical relational learning
D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ...
MIT press, 2007
17632007
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
5952007
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
3642018
A convolutional attention network for extreme summarization of source code
M Allamanis, H Peng, C Sutton
International conference on machine learning, 2091-2100, 2016
3162016
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
2982017
Learning natural coding conventions
M Allamanis, ET Barr, C Bird, C Sutton
Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations …, 2014
2962014
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
2912015
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
2732009
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
2652008
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
2612013
Piecewise training for undirected models
C Sutton, A McCallum
arXiv preprint arXiv:1207.1409, 2012
2242012
Autoencoding variational inference for topic models
A Srivastava, C Sutton
arXiv preprint arXiv:1703.01488, 2017
2132017
Collective segmentation and labeling of distant entities in information extraction
C Sutton, A McCallum
MASSACHUSETTS UNIV AMHERST DEPT OF COMPUTER SCIENCE, 2004
1672004
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
1542009
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
1522018
Mining idioms from source code
M Allamanis, C Sutton
Proceedings of the 22nd acm sigsoft international symposium on foundations …, 2014
1432014
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
1332007
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
1252013
Gemsec: Graph embedding with self clustering
B Rozemberczki, R Davies, R Sarkar, C Sutton
Proceedings of the 2019 IEEE/ACM international conference on advances in …, 2019
1032019
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