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Beyond Size and Class Balance: Alpha as a New Dataset Quality Metric for Deep Learning
By analyzing thousands of subsets from seven medical datasets representing ultrasound, X-ray, CT, and pathology images, we found that the best correlates of performance were not size or class balance but $A$ -- ``big alpha'' -- a set of generalized entropy measures interpreted as the effective number of image-class pairs in the dataset, after accounting for similarities among images.
Scaling Monte-Carlo-Based Inference on Antibody and TCR Repertoires
We demonstrate that this new method enables the generation of accurate estimates for 27 models using only three expensive estimates, thereby reducing the computational cost by an order of magnitude.
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