‪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 DameVerificeret mail på nd.edu
Lawrence HallProfessor of Computer Science and Engineering, University of South FloridaVerificeret mail på usf.edu
Chuxu ZhangAssociate Professor of CSE, University of Connecticut (UConn)Verificeret mail på uconn.edu
William Philip KegelmeyerSandia National LaboratoriesVerificeret mail på sandia.gov
Yuxiao DongCS, Tsinghua UniversityVerificeret mail på tsinghua.edu.cn
Chao HuangAssistant Professor of Computer Science, University of Hong KongVerificeret mail på hku.hk
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Meng JiangUniversity of Notre DameVerificeret mail på nd.edu
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Tang JieWeBank Chair Professor, Tsinghua UniversityVerificeret mail på tsinghua.edu.cn
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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

Verificeret mail på nd.edu - Startside

Data science artificial intelligence network science


Titel Sortér efter henvisninger Sortér efter årstal Sortér efter titel	Citeret af Citeret af	År
SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002	34243	2002
Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004	3067	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	2672	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	2261	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	2065	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	1199	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	420	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	365	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	351	2015

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