 In this few-samples regime, it substantially outperforms standard machine learning methods such as nearest-neighbors, support-vector machines, and convolutional neural networks ( CNNs) .
<meaning-changed>  In this few-samples regime, it substantially outperforms standard machine learning methods such as nearest-neighbors, support-vector machines, and convolutional neural networks ( CNNs) .
 In this few-samples regime, it substantially outperforms standard machine learning methods such as nearest-neighbors, support-vector machines, and convolutional neural networks ( NNs), and matches specialized one-shot transfer-learning methods but without the need for pre-training .