| SMOTE: synthetic minority over-sampling technique NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002 | 41586 | 2002 |
| Special issue on learning from imbalanced data sets NV Chawla, N Japkowicz, A Kotcz ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004 | 3188 | 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 | 3048 | 2017 |
| 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 | 2703 | 2018 |
| 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 | 2426 | 2003 |
| Data mining for imbalanced datasets: An overview NV Chawla Data mining and knowledge discovery handbook, 875-886, 2010 | 2324 | 2010 |
| 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 | 2001 | 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 | 1504 | 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 | 1252 | 2008 |
| Large language model based multi-agents: A Survey of Progress and Challenges T Guo, X Chen, Y Wang, R Chang, S Pei, NV Chawla, O Wiest, X Zhang Proceedings of the Thirty-Third International Joint Conference on Artificial …, 2024 | 1219 | 2024 |
| 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 | 1200 | 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 | 943 | 2010 |
| Bringing big data to personalized healthcare: a patient-centered framework NV Chawla, DA Davis Journal of general internal medicine 28 (Suppl 3), 660-665, 2013 | 653 | 2013 |
| 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 | 624 | 2022 |
| Combating imbalance in network intrusion datasets. DA Cieslak, NV Chawla, A Striegel GrC, 732-737, 2006 | 453 | 2006 |
| Learning decision trees for unbalanced data DA Cieslak, NV Chawla Joint European conference on machine learning and knowledge discovery in …, 2008 | 436 | 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 | 433 | 2012 |
| 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 | 430 | 2003 |
| G-retriever: Retrieval-augmented generation for textual graph understanding and question answering X He, Y Tian, Y Sun, N Chawla, T Laurent, Y LeCun, X Bresson, B Hooi Advances in Neural Information Processing Systems 37, 132876-132907, 2024 | 404 | 2024 |
| Evaluating link prediction methods Y Yang, RN Lichtenwalter, NV Chawla Knowledge and Information Systems 45 (3), 751-782, 2015 | 388 | 2015 |
Kevin W. BowyerSchubmehl-Prein Family Professor of Computer Science and Engineering, University of Notre DameVerified email at nd.edu
