AINeutralarXiv – CS AI · 7h ago6/10
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Why Not Hyperparameter-Friendly Optimisation? A Monotonic Adaptive Norm Rescaling Approach For Long-Tailed Recognition
Researchers propose Self-Adaptive Monotonic Normalization (SAMN), a hyperparameter-friendly approach to improve long-tailed recognition in deep learning. The method eliminates the need for manual parameter tuning while achieving state-of-the-art performance by enforcing monotonic constraints on per-class weight norms during classifier retraining.