Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss

Explore effective strategies for handling imbalanced datasets using the Label-Distribution-Aware Margin Loss in this informative 23-minute lecture from the University of Central Florida. Gain insights into the challenges posed by data imbalance, understand existing solutions, and delve into experimental results that demonstrate the effectiveness of this novel approach. Learn how to improve model performance on imbalanced datasets, a common issue in real-world machine learning applications.