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Nitesh V Chawla, Fellow: ACM, IEEE, AAAS, AAAI
Nitesh V Chawla, Fellow: ACM, IEEE, AAAS, AAAI
Frank Freimann Professor of CSE.,Director, Lucy Family Institute for Data & Soc, Univ. of Notre Dame
Verifierad e-postadress på nd.edu - Startsida
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SMOTE: synthetic minority over-sampling technique
NV Chawla, KW Bowyer, LO Hall, WP Kegelmeyer
Journal of Artificial Intelligence Research (JAIR) 16, 321-357, 2002
329502002
Special issue on learning from imbalanced data sets
NV Chawla, N Japkowicz, A Kotcz
ACM SIGKDD explorations newsletter 6 (1), 1-6, 2004
30382004
metapath2vec: Scalable representation learning for heterogeneous networks
Y Dong, NV Chawla, A Swami
Proceedings of the 23rd ACM SIGKDD international conference on knowledge …, 2017
25982017
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
22212003
Data mining for imbalanced datasets: An overview
NV Chawla
Data mining and knowledge discovery handbook, 875-886, 2010
21762010
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
19512018
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
15002019
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
12422012
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
11812008
New perspectives and methods in link prediction
RN Lichtenwalter, JT Lussier, NV Chawla
Proceedings of the 16th ACM SIGKDD international conference on Knowledge …, 2010
9142010
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
9052019
Bringing big data to personalized healthcare: a patient-centered framework
NV Chawla, DA Davis
Journal of general internal medicine 28, 660-665, 2013
6172013
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
4252003
Learning decision trees for unbalanced data
DA Cieslak, NV Chawla
Machine Learning and Knowledge Discovery in Databases: European Conference …, 2008
4092008
Combating imbalance in network intrusion datasets.
DA Cieslak, NV Chawla, A Striegel
GrC, 732-737, 2006
4052006
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
3932012
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
3742014
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
3602012
Evaluating link prediction methods
Y Yang, RN Lichtenwalter, NV Chawla
Knowledge and Information Systems 45, 751-782, 2015
3362015
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
3252008
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