Gradient-Descent Steps to Success over Mean Accuracy: A Paradigm Shift for ML

Traditional evaluation of machine learning (ML) models typically focuses on achieving the maximum possible accuracy irrespective of the computational cost. In this article, we propose a paradigm shift towards evaluating performance based on computational effort-explicitly defined here as the total n…

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