Daniel Lowd

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Pedro DomingosProfessor of Computer Science and Engineering, University of WashingtonVerified email at cs.washington.edu
Dejing DouProfessor (on leave), University of Oregon/Head of BDL and BIL, Baidu ResearchVerified email at cs.uoregon.edu
Hoifung PoonSenior Director, Biomedical NLP, Microsoft ResearchVerified email at microsoft.com
Matthew RichardsonMicrosoft ResearchVerified email at microsoft.com
Parag SinglaIndian Institute of Technology DelhiVerified email at cse.iitd.ac.in
Stanley KokNational University of SingaporeVerified email at nus.edu.sg
Javid EbrahimiVisa ResearchVerified email at visa.com
Pedram RooshenasUNC CharlotteVerified email at uncc.edu
Christopher MeekPrinciple Researcher, Microsoft ResearchVerified email at microsoft.com
Anyi RaoMMLab, CUHKVerified email at ie.cuhk.edu.hk
Aniruddh NathGoogle, LLCVerified email at google.com
Ali TorkamaniUniversity of Oregon, Cambia Health Solutions, Amazon Web ServicesVerified email at amazon.com
Jesse DavisProfessor, Department of Computer Science, KU LeuvenVerified email at cs.kuleuven.be
Sriraam NatarajanUniversity of Texas at DallasVerified email at utdallas.edu
Kristian KerstingProfessor of AI & Machine Learning, TU Darmstadt, Co-Director of hessian.ai, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Prasad TadepalliProfessor of Computer Science, Oregon State UniversityVerified email at eecs.oregonstate.edu
Tushar KhotAllen Institute for AI; University of Wisconsin-MadisonVerified email at cs.wisc.edu
Jude ShavlikProfessor of Computer Science and of Biostatistics & Medical Informatics, University of WisconsinVerified email at cs.wisc.edu
Reza RejaieProfessor of Computer and Information Science, University of OregonVerified email at cs.uoregon.edu
Adam BatesAssistant Professor, University of Illinois at Urbana-ChampaignVerified email at illinois.edu

Daniel Lowd

Associate Professor of Computer Science, University of Oregon

Verified email at cs.uoregon.edu - Homepage

Machine learning artificial intelligence


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Adversarial learning D Lowd, C Meek Proceedings of the eleventh ACM SIGKDD international conference on Knowledge …, 2005	813	2005
Markov logic: An interface layer for artificial intelligence P Domingos, D Lowd Synthesis Lectures on Artificial Intelligence and Machine Learning 3 (1), 1-155, 2009	587	2009
Hotflip: White-box adversarial examples for text classification J Ebrahimi, A Rao, D Lowd, D Dou arXiv preprint arXiv:1712.06751, 2017	578	2017
Naive Bayes models for probability estimation D Lowd, P Domingos Proceedings of the 22nd international conference on Machine learning, 529-536, 2005	379	2005
Good word attacks on statistical spam filters D Lowd, C Meek Proceedings of the second conference on email and anti-spam (CEAS), 125-132, 2005	364	2005
The Alchemy system for statistical relational AI S Kok, P Singla, M Richardson, P Domingos, M Sumner, H Poon, D Lowd University of Washington, Seattle, 2005	359	2005
Efficient weight learning for Markov logic networks D Lowd, P Domingos Knowledge Discovery in Databases: PKDD 2007, 200-211, 2007	309	2007
Neural-symbolic learning and reasoning: A survey and interpretation TR Besold, AA Garcez, S Bader, H Bowman, P Domingos, P Hitzler, ... arXiv preprint arXiv:1711.03902, 2017	162	2017
Learning sum-product networks with direct and indirect variable interactions A Rooshenas, D Lowd International Conference on Machine Learning, 710-718, 2014	157	2014
Unifying logical and statistical AI P Domingos, D Lowd, S Kok, A Nath, H Poon, M Richardson, P Singla 2016 31st Annual ACM/IEEE Symposium on Logic in Computer Science (LICS), 1-11, 2016	155	2016
On adversarial examples for character-level neural machine translation J Ebrahimi, D Lowd, D Dou arXiv preprint arXiv:1806.09030, 2018	134	2018
Learning arithmetic circuits D Lowd, P Domingos Proc. UAI 8, 383-392, 2008	108*	2008
Markov logic P Domingos, S Kok, D Lowd, H Poon, M Richardson, P Singla Probabilistic inductive logic programming, 92-117, 2008	100	2008
Learning Markov network structure with decision trees D Lowd, J Davis Data Mining (ICDM), 2010 IEEE 10th International Conference on, 334-343, 2010	91	2010
Learning to refine an automatically extracted knowledge base using markov logic S Jiang, D Lowd, D Dou 2012 IEEE 12th International Conference on Data Mining, 912-917, 2012	74	2012
Learning Markov Networks With Arithmetic Circuits D Lowd, A Rooshenas 16th International Conference on Artificial Intelligence and Statistics …, 2013	73	2013
Weakly supervised tweet stance classification by relational bootstrapping J Ebrahimi, D Dou, D Lowd Proceedings of the 2016 conference on empirical methods in natural language …, 2016	58	2016
Just add weights: Markov logic for the semantic web P Domingos, D Lowd, S Kok, H Poon, M Richardson, P Singla Uncertainty Reasoning for the Semantic Web I, 1-25, 2006	53	2006
A joint sentiment-target-stance model for stance classification in tweets J Ebrahimi, D Dou, D Lowd Proceedings of COLING 2016, the 26th International Conference on …, 2016	51	2016
Improving Markov network structure learning using decision trees D Lowd, J Davis The Journal of Machine Learning Research 15 (1), 501-532, 2014	42	2014

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