| SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002 | 18793 | 2002 |
| Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004 | 2480 | 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 | 1728 | 2003 |
| Data mining for imbalanced datasets: An overview NV Chawla Data mining and knowledge discovery handbook, 875-886, 2009 | 1670 | 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 | 1384 | 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 | 955 | 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 | 821 | 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 | 676 | 2018 |
| 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 | 614 | 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 | 467 | 2013 |
| 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 | 429 | 2019 |
| 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 | 370 | 2003 |
| Learning decision trees for unbalanced data DA Cieslak, NV Chawla Joint European Conference on Machine Learning and Knowledge Discovery in …, 2008 | 321 | 2008 |
| 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 | 284 | 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 | 283 | 2014 |
| 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 | 283 | 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 | 280 | 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 | 278 | 2012 |
| 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 | 272 | 2019 |
| Combating imbalance in network intrusion datasets. DA Cieslak, NV Chawla, A Striegel GrC, 732-737, 2006 | 266 | 2006 |
Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre Damend.edu의 이메일 확인됨
