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cs.LG2025
Orthogonal Activation with Implicit Group-Aware Bias Learning for Class Imbalance
Sukumar Kishanthan, Asela Hevapathige
Class imbalance is a common challenge in machine learning and data mining, often leading to suboptimal performance in classifiers. While deep learning excels in feature extraction,…
cs.LG2025
AxelSMOTE: An Agent-Based Oversampling Algorithm for Imbalanced Classification
Sukumar Kishanthan, Asela Hevapathige
Class imbalance in machine learning poses a significant challenge, as skewed datasets often hinder performance on minority classes. Traditional oversampling techniques, which are c…
cs.LG2025
Deep Learning Meets Oversampling: A Learning Framework to Handle Imbalanced Classification
Sukumar Kishanthan, Asela Hevapathige
Despite extensive research spanning several decades, class imbalance is still considered a profound difficulty for both machine learning and deep learning models. While data oversa…