Nitesh V. Chawla

SMOTE for Learning from Imbalanced Data: Progress and Challenges, Marking the 15-year Anniversary

2018 · Journal of Artificial Intelligence Research

The Synthetic Minority Oversampling Technique (SMOTE) preprocessing algorithm is considered "de facto" standard in the framework of learning from imbalanced data. This is due to its simplicity in the design of the procedure, as well …

Boosting Graph Neural Networks via Adaptive Knowledge Distillation

2022 · arXiv (Cornell University)

Graph neural networks (GNNs) have shown remarkable performance on diverse graph mining tasks. Although different GNNs can be unified as the same message passing framework, they learn complementary knowledge from the same graph. Knowledge distillation …

Online Purchase Prediction via Multi-Scale Modeling of Behavior Dynamics

2019

Online purchase forecasting is of great importance in e-commerce platforms, which is the basis of how to present personalized interesting product lists to individual customers. However, predicting online purchases is not trivial as it is …