Charles Elkan

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Timothy BaileyUniversity of Nevada, RenoVerified email at unr.edu
Zachary C. LiptonRaj Reddy Associate Professor of Machine Learning @ Carnegie Mellon University; CTO + CSO @ AbridgeVerified email at cmu.edu
Balakrishnan NarayanaswamyPrincipal ML Scientist, AWS AI, AmazonVerified email at amazon.com
Aditya Krishna MenonResearch Scientist, GoogleVerified email at google.com
Bianca ZadroznyIBM Research BrasilVerified email at br.ibm.com
Alvaro MongeTeaching Professor, Northeastern University, Oakland CaliforniaVerified email at northeastern.edu
David KauchakProfessor of Computer Science, Pomona CollegeVerified email at pomona.edu
Milton SaierProfessor of Molecular Biology, UC San DiegoVerified email at ucsd.edu
Dave KaleData Science Manager, LiteratiVerified email at literati.com
Ramon HuertaSenior Principal Scientist, AmazonVerified email at amazon.com
Alberto Maria SegreProfessor and Chair, Gerard P Weeg Faculty Scholar in Informatics, Department of Computer ScienceVerified email at uiowa.edu
Rasmus Elsborg MadsenUNEEG medicalVerified email at uneeg.com
Qinghua GuoPeking UniversityVerified email at pku.edu.cn
Wenkai LiSun Yat-Sen UniversityVerified email at mail.sysu.edu.cn
Rashmi GangadharaiahPrincipal Machine Learning Scientist, AmazonVerified email at amazon.com
Garrison CottrellComputer Science and Engineering, UCSDVerified email at ucsd.edu
Padhraic SmythDistinguished Professor, Computer Science, University of California IrvineVerified email at ics.uci.edu
Lotfi A. ZadehProfessor Emeritus, EECS, UC BerkeleyVerified email at eecs.berkeley.edu
Gabriel DoyleAssistant Professor, San Diego State UniversityVerified email at sdsu.edu
Russ GreinerProfessor of Computing Science, University of Alberta; CIFAR AI ChairVerified email at ualberta.ca

Charles Elkan

Professor of Computer Science, University of California, San Diego

Verified email at ucsd.edu

Machine Learning Data Science Finance


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Fitting a mixture model by expectation maximization to discover motifs in biopolymers TL Bailey, C Elkan ISMB, 28-36, 1994	6437	1994
A critical review of recurrent neural networks for sequence learning ZC Lipton, J Berkowitz, C Elkan arXiv preprint arXiv:1506.00019, 2015	3652	2015
The foundations of cost-sensitive learning C Elkan International joint conference on artificial intelligence 17 (1), 973-978, 2001	3271	2001
Transforming classifier scores into accurate multiclass probability estimates B Zadrozny, C Elkan Proceedings of the eighth ACM SIGKDD international conference on Knowledge …, 2002	1638	2002
Learning to diagnose with LSTM recurrent neural networks ZC Lipton, DC Kale, C Elkan, R Wetzel arXiv preprint arXiv:1511.03677, 2015	1518	2015
Learning the k in k-means G Hamerly, C Elkan Advances in neural information processing systems 16: proceedings of the …, 2004	1482	2004
Learning classifiers from only positive and unlabeled data C Elkan, K Noto Proceedings of the 14th ACM SIGKDD international conference on Knowledge …, 2008	1340	2008
Obtaining calibrated probability estimates from decision trees and naive Bayesian classifiers B Zadrozny, C Elkan ICML, 609-616, 2001	1270	2001
Using the triangle inequality to accelerate k-means C Elkan Proceedings of the 20th international conference on Machine Learning (ICML …, 2003	1241	2003
Unsupervised learning of multiple motifs in biopolymers using expectation maximization TL Bailey, C Elkan Machine Learning 21 (1), 51-80, 1995	998	1995
The value of prior knowledge in discovering motifs with MEME. TL Bailey, C Elkan Ismb 3, 21-29, 1995	926	1995
The field matching problem: algorithms and applications AE Monge, C Elkan KDD 2, 267-270, 1996	901	1996
Alternatives to the k-means algorithm that find better clusterings G Hamerly, C Elkan Proceedings of the eleventh international conference on Information and …, 2002	804	2002
Link prediction via matrix factorization AK Menon, C Elkan Machine Learning and Knowledge Discovery in Databases: European Conference …, 2011	723	2011
Learning and making decisions when costs and probabilities are both unknown B Zadrozny, C Elkan Proceedings of the seventh ACM SIGKDD international conference on Knowledge …, 2001	676	2001
An efficient domain-independent algorithm for detecting approximately duplicate database records AE Monge Proc. of the ACM-SIGMOD Workshop on Research Issues on Knowledge Discovery …, 1997	628	1997
Optimal thresholding of classifiers to maximize F1 measure ZC Lipton, C Elkan, B Naryanaswamy Machine Learning and Knowledge Discovery in Databases: European Conference …, 2014	537	2014
The transporter classification database: recent advances MH Saier Jr, MR Yen, K Noto, DG Tamang, C Elkan Nucleic acids research 37 (suppl_1), D274-D278, 2009	508	2009
The paradoxical controversy over fuzzy logic C Elkan IEEE Intelligent Systems, 47-49, 1994	468*	1994
The paradoxical success of fuzzy logic C Elkan, HR Berenji, B Chandrasekaran, CJS De Silva, Y Attikiouzel, ... IEEE Expert 9 (4), 3-49, 1994	467	1994

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