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Theoretical optimization of group size in group normalization for enhanced deep neural network training

Neural Scaling LawTheoretical OptimizationEngineeringMachine LearningGroup NormalizationSparse Neural NetworkData NormalizationGroup SizeDeep LearningFeature Scaling