Computer Science
Predicting trends in the quality of state-of-the-art neural networks without access to training or testing data
C. H. Martin, T. (. Peng, et al.
Discover groundbreaking insights from Charles H. Martin, Tongsu (Serena) Peng, and Michael W. Mahoney as they tackle the daunting challenge of evaluating pre-trained neural network models without any access to training data. Their research reveals that power law-based metrics significantly outperform traditional measures in distinguishing model quality and uncovering hidden issues.
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