<ul><li>The experimental results on linear and housing datasets evaluate the performance of ADA (Anchor Data Augmentation).</li><li>In the in-distribution setting for a linear regression problem, ADA shows improved performance in the low data regime.</li><li>ADA and C-Mixup are applied to the California and Boston Housing datasets, analyzing the impact on model performance as the number of training samples increases.</li><li>ADA and C-Mixup provide gains in performance even in cases where the number of training examples is not sufficient to achieve the error floor.</li></ul>

Evaluating ADA: Experimental Results on Linear and Housing Datasets

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