‪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 Dame在 nd.edu 的电子邮件经过验证
Lawrence HallProfessor of Computer Science and Engineering, University of South Florida在 usf.edu 的电子邮件经过验证
Chuxu ZhangAssociate Professor of CSE, University of Connecticut (UConn)在 uconn.edu 的电子邮件经过验证
William Philip KegelmeyerSandia National Laboratories在 sandia.gov 的电子邮件经过验证
Yuxiao DongCS, Tsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
Chao HuangAssistant Professor of Computer Science, University of Hong Kong在 hku.hk 的电子邮件经过验证
David CieslakVP of Predictive Modeling在 aunalytics.com 的电子邮件经过验证
Meng JiangUniversity of Notre Dame在 nd.edu 的电子邮件经过验证
Karsten SteinhaeuserComputer Science and Engineering, University of Minnesota在 umn.edu 的电子邮件经过验证
Yang YangMendoza College of Business, University of Notre Dame在 nd.edu 的电子邮件经过验证
Troy RaederTwo Sigma在 twosigma.com 的电子邮件经过验证
Auroop R GangulyCOE Distinguished Professor, Fellow ASCE, Distinguished Member ACM, Northeastern University, Boston在 northeastern.edu 的电子邮件经过验证
Xian WuUniversity of Notre Dame, Pinterest在 alumni.nd.edu 的电子邮件经过验证
Jian Xu 徐健Senior Data Scientist @ Citadel | Ph.D. in Computer Science在 jianxu.net 的电子邮件经过验证
Keith FeldmanChildren's Mercy Kansas City在 cmh.edu 的电子邮件经过验证
Aaron StriegelProfessor, Department of Computer Science and Engineering, University of Notre Dame在 nd.edu 的电子邮件经过验证
Reid A. JohnsonZillow Group在 nd.edu 的电子邮件经过验证
Louis FaustAssistant Professor of Biomedical Informatics, Mayo Clinic在 mayo.edu 的电子邮件经过验证
Tang JieWeBank Chair Professor, Tsinghua University在 tsinghua.edu.cn 的电子邮件经过验证
David HachenProfessor of Sociology, University of Notre Dame在 nd.edu 的电子邮件经过验证

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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

在 nd.edu 的电子邮件经过验证 - 首页

Data science machine learning network science


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002	31276	2002
Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004	2981	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	2484	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	2184	2003
Data mining for imbalanced datasets: An overview NV Chawla Data mining and knowledge discovery handbook, 875-886, 2010	2125	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	1786	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	1400	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	1167	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	1158	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	907	2010
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	840	2019
Bringing big data to personalized healthcare: a patient-centered framework NV Chawla, DA Davis Journal of general internal medicine 28, 660-665, 2013	596	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	419	2003
Learning decision trees for unbalanced data DA Cieslak, NV Chawla Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008	399	2008
Combating imbalance in network intrusion datasets. DA Cieslak, NV Chawla, A Striegel GrC, 732-737, 2006	393	2006
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	386	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	370	2014
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	355	2012
Evaluating link prediction methods Y Yang, RN Lichtenwalter, NV Chawla Knowledge and Information Systems 45, 751-782, 2015	323	2015
Automatically countering imbalance and its empirical relationship to cost NV Chawla, DA Cieslak, LO Hall, A Joshi Data Mining and Knowledge Discovery 17, 225-252, 2008	321	2008

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