Nitesh V. Chawla

Nitesh V. Chawla is a person.

• See: Imbalanced Supervised Training Dataset, Neural Outlier Detection.

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References

• https://scholar.google.com/citations?user=hDLBEhkAAAAJ&hl=en

2019

• (Zhang, Song et al., 2019) ⇒ Chuxu Zhang, Dongjin Song, Yuncong Chen, Xinyang Feng, Cristian Lumezanu, Wei Cheng, Jingchao Ni, Bo Zong, Haifeng Chen, and Nitesh V. Chawla. (2019). “A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.” In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 33.
• (Jiang, Zhao et al., 2019) ⇒ Tianwen Jiang, Tong Zhao, Bing Qin, Ting Liu, Nitesh V. Chawla, and Meng Jiang. (2019). “The Role of" Condition" A Novel Scientific Knowledge Graph Representation and Construction Model.” In: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery \& Data Mining.

2017

• (Dong et al., 2017) ⇒ Yuxiao Dong, Nitesh V. Chawla, and Ananthram Swami. (2017). “metapath2vec: Scalable Representation Learning for Heterogeneous Networks.” In: Proceedings of the 23rd ACM SIGKDD International Conference on knowledge discovery and data mining (SIGKDD-2017).

2010

• (Lichtenwalter et al., 2010) ⇒ Ryan N. Lichtenwalter, Jake T. Lussier, and Nitesh V. Chawla. (2010). “New Perspectives and Methods in Link Prediction.” In: Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2010). doi:10.1145/1835804.1835837

2004

• (Chawla et al., 2004) ⇒ Nitesh Chawla, Nathalie Japkowicz, Aleksander Kolcz. (2004). “Editorial: Special issue on learning from imbalanced data sets.” In: ACM SIGKDD Explorations Newsletter, 6(1). doi:10.1145/1007730.1007733

2002

• (Chawla et al., 2002) ⇒ Nitesh V. Chawla, Kevin W. Bowyer, Lawrence O. Hall, and W. Philip Kegelmeyer. (2002). “SMOTE: Synthetic Minority over-sampling Technique.” In: Journal of Artificial Intelligence Research, 16(1).

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