Orthogonal Activation with Implicit Group-Aware Bias Learning for Class Imbalance
Published:Dec 23, 2025 03:05
•1 min read
•ArXiv
Analysis
This article presents a research paper on a method to address class imbalance in machine learning. The core technique involves orthogonal activation and implicit group-aware bias learning. The focus is on improving model performance when dealing with datasets where some classes have significantly fewer examples than others.
Key Takeaways
- •Addresses the problem of class imbalance in machine learning.
- •Proposes a novel method using orthogonal activation and implicit group-aware bias learning.
- •Aims to improve model performance on imbalanced datasets.
Reference
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