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combines new samples with ratio 1:1 using concat. Key Insights: The results are promising. Batchboost has 0.5–3% better accuracy than the current state-of-the-art mixup regularization on CIFAR-10 (#10 place in paperswithcode.com) & Fashion-MNIST. (we hope to see our method in action, for example,