Nitesh V Chawla

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Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre DameVerified email at nd.edu
Lawrence HallProfessor of Computer Science and Engineering, University of South FloridaVerified email at mail.usf.edu
William Philip KegelmeyerSandia National LaboratoriesVerified email at sandia.gov
Yuxiao DongMicrosoft ResearchVerified email at microsoft.com
David CieslakVP of Predictive ModelingVerified email at aunalytics.com
Karsten SteinhaeuserResearch Associate in Computer Science and Engineering, University of MinnesotaVerified email at umn.edu
Yang YangKellogg School of ManagementVerified email at kellogg.northwestern.edu
Chao HuangUniversity of Notre DameVerified email at nd.edu
Auroop GangulyProfessor, Northeastern University, Boston, MAVerified email at neu.edu
Chuxu ZhangAssistant Professor, Computer Science, Brandeis UniversityVerified email at brandeis.edu
Troy RaederDstilleryVerified email at dstillery.com
Jian Xu 徐健Data Scientist @ Citadel | Ph.D. in Computer ScienceVerified email at jianxu.net
Keith FeldmanUniversity of Notre DameVerified email at nd.edu
Aaron StriegelProfessor, Department of Computer Science and Engineering, University of Notre DameVerified email at nd.edu
David HachenProfessor of Sociology, University of Notre DameVerified email at nd.edu
Omar LizardoUniversity of California, Los AngelesVerified email at soc.ucla.edu
Tang JieProfessor of Data Mining, Tsinghua UniversityVerified email at tsinghua.edu.cn
Jiawei HanAbel Bliss Professor of Computer Science, University of IllinoisVerified email at cs.uiuc.edu
Louis FaustUniversity of Notre DameVerified email at nd.edu
Francisco HerreraProfessor Computer Science and AI, Granada Univ.; Senior Associate Researcher in DL&ML at Sherpa.aiVerified email at decsai.ugr.es

Nitesh V Chawla

Frank Freimann Professor of Computer Science & Engg., Notre Dame

Verified email at nd.edu - Homepage

Data science machine learning data mining network science


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SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002	14691	2002
Data mining and knowledge discovery handbook O Maimon, L Rokach Springer 2 (2005), 2005	2409	2005
Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004	2271	2004
SMOTEBoost: Improving prediction of the minority class in boosting NV Chawla, A Lazarevic, LO Hall, KW Bowyer European conference on principles of data mining and knowledge discovery …, 2003	1509	2003
Data mining for imbalanced datasets: An overview NV Chawla Data mining and knowledge discovery handbook, 875-886, 2009	1457	2009
metapath2vec: Scalable representation learning for heterogeneous networks Y Dong, NV Chawla, A Swami Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017	948	2017
SVMs modeling for highly imbalanced classification Y Tang, YQ Zhang, NV Chawla, S Krasser IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2008	874	2008
New perspectives and methods in link prediction RN Lichtenwalter, JT Lussier, NV Chawla Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	753	2010
A unifying view on dataset shift in classification JG Moreno-Torres, T Raeder, R Alaiz-Rodríguez, NV Chawla, F Herrera Pattern recognition 45 (1), 521-530, 2012	454	2012
Bringing big data to personalized healthcare: a patient-centered framework NV Chawla, DA Davis Journal of general internal medicine 28 (3), 660-665, 2013	416	2013
SMOTE for learning from imbalanced data: progress and challenges, marking the 15-year anniversary A Fernández, S Garcia, F Herrera, NV Chawla Journal of artificial intelligence research 61, 863-905, 2018	386	2018
C4. 5 and imbalanced data sets: investigating the effect of sampling method, probabilistic estimate, and decision tree structure NV Chawla Proceedings of the ICML 3, 66, 2003	351	2003
Learning decision trees for unbalanced data DA Cieslak, NV Chawla Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008	291	2008
When will it happen? relationship prediction in heterogeneous information networks Y Sun, J Han, CC Aggarwal, NV Chawla Proceedings of the fifth ACM international conference on Web search and data …, 2012	267	2012
Link prediction and recommendation across heterogeneous social networks Y Dong, J Tang, S Wu, J Tian, NV Chawla, J Rao, H Cao 2012 IEEE 12th International conference on data mining, 181-190, 2012	259	2012
Automatically countering imbalance and its empirical relationship to cost NV Chawla, DA Cieslak, LO Hall, A Joshi Data Mining and Knowledge Discovery 17 (2), 225-252, 2008	256	2008
Learning from streaming data with concept drift and imbalance: an overview TR Hoens, R Polikar, NV Chawla Progress in Artificial Intelligence 1 (1), 89-101, 2012	240	2012
Big data opportunities and challenges: Discussions from data analytics perspectives [discussion forum] ZH Zhou, NV Chawla, Y Jin, GJ Williams IEEE Computational intelligence magazine 9 (4), 62-74, 2014	234	2014
Combating imbalance in network intrusion datasets. DA Cieslak, NV Chawla, A Striegel GrC, 732-737, 2006	212	2006
Identifying and evaluating community structure in complex networks K Steinhaeuser, NV Chawla Pattern Recognition Letters 31 (5), 413-421, 2010	211	2010

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