‪Nitesh V Chawla, Fellow: ACM, IEEE, AAAS, AAAI‬

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Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre DameEmail verificata su nd.edu
Lawrence HallProfessor of Computer Science and Engineering, University of South FloridaEmail verificata su usf.edu
Chuxu ZhangAssociate Professor of CSE, University of Connecticut (UConn)Email verificata su uconn.edu
William Philip KegelmeyerSandia National LaboratoriesEmail verificata su sandia.gov
Yuxiao DongCS, Tsinghua UniversityEmail verificata su tsinghua.edu.cn
Chao HuangAssistant Professor of Computer Science, University of Hong KongEmail verificata su hku.hk
David CieslakVP of Predictive ModelingEmail verificata su aunalytics.com
Meng JiangUniversity of Notre DameEmail verificata su nd.edu
Yang YangMendoza College of Business, University of Notre DameEmail verificata su nd.edu
Karsten SteinhaeuserComputer Science and Engineering, University of MinnesotaEmail verificata su umn.edu
Troy RaederTwo SigmaEmail verificata su twosigma.com
Xian WuUniversity of Notre Dame, PinterestEmail verificata su alumni.nd.edu
Keith FeldmanChildren's Mercy Kansas CityEmail verificata su cmh.edu
Jian Xu 徐健Senior Data Scientist @ Citadel | Ph.D. in Computer ScienceEmail verificata su jianxu.net
Auroop R GangulyCOE Distinguished Professor, Fellow ASCE, Distinguished Member ACM, Northeastern University, BostonEmail verificata su northeastern.edu
Aaron StriegelProfessor, Department of Computer Science and Engineering, University of Notre DameEmail verificata su nd.edu
Reid A. JohnsonZillow GroupEmail verificata su nd.edu
Louis FaustAssistant Professor of Biomedical Informatics, Mayo ClinicEmail verificata su mayo.edu
Tang JieWeBank Chair Professor, Tsinghua UniversityEmail verificata su tsinghua.edu.cn
David HachenProfessor of Sociology, University of Notre DameEmail verificata su nd.edu

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Nitesh V Chawla, Fellow: ACM, IEEE, AAAS, AAAI

Frank Freimann Professor of CSE.,Director, Lucy Family Institute for Data & Soc, Univ. of Notre Dame

Email verificata su nd.edu - Home page

Data science artificial intelligence network science


Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002	34207	2002
Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004	3066	2004
metapath2vec: Scalable representation learning for heterogeneous networks Y Dong, NV Chawla, A Swami Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017	2669	2017
SMOTEBoost: Improving prediction of the minority class in boosting NV Chawla, A Lazarevic, LO Hall, KW Bowyer Knowledge Discovery in Databases: PKDD 2003: 7th European Conference on …, 2003	2257	2003
Data mining for imbalanced datasets: An overview NV Chawla Data mining and knowledge discovery handbook, 875-886, 2010	2203	2010
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	2059	2018
Heterogeneous graph neural network C Zhang, D Song, C Huang, A Swami, NV Chawla Proceedings of the 25th ACM SIGKDD international conference on knowledge …, 2019	1585	2019
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	1274	2012
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	1196	2008
A deep neural network for unsupervised anomaly detection and diagnosis in multivariate time series data C Zhang, D Song, Y Chen, X Feng, C Lumezanu, W Cheng, J Ni, B Zong, ... Proceedings of the AAAI conference on artificial intelligence 33 (01), 1409-1416, 2019	958	2019
New perspectives and methods in link prediction RN Lichtenwalter, JT Lussier, NV Chawla Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010	917	2010
Bringing big data to personalized healthcare: a patient-centered framework NV Chawla, DA Davis Journal of general internal medicine 28, 660-665, 2013	626	2013
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	427	2003
Combating imbalance in network intrusion datasets. DA Cieslak, NV Chawla, A Striegel GrC, 732-737, 2006	418	2006
Learning decision trees for unbalanced data DA Cieslak, NV Chawla Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008	412	2008
Learning from streaming data with concept drift and imbalance: an overview TR Hoens, R Polikar, NV Chawla Progress in Artificial Intelligence 1, 89-101, 2012	403	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	379	2014
DeepSMOTE: Fusing deep learning and SMOTE for imbalanced data D Dablain, B Krawczyk, NV Chawla IEEE Transactions on Neural Networks and Learning Systems 34 (9), 6390-6404, 2022	362	2022
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	362	2012
Evaluating link prediction methods Y Yang, RN Lichtenwalter, NV Chawla Knowledge and Information Systems 45, 751-782, 2015	349	2015

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