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Mitigating Bias in Dataset Distillation

By Justin Cui and others
Dataset Distillation has emerged as a technique for compressing large datasets into smaller synthetic counterparts, facilitating downstream training tasks. In this paper, we study the impact of bias inside the original dataset on the performance of dataset distillation. With a comprehensive empirical evaluation on canonical datasets with color, corruption and... Show more
July 10, 2024
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Mitigating Bias in Dataset Distillation
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