Liwen You

Oct 6, 2023 | amazon.science | Yun Zhou |Liwen You |Wenzhen Zhu |Panpan Xu

Mixup is a domain-agnostic approach for data augmentation, originally proposed for training Deep Neural Networks (DNNs) for image classification. It obtains additional data for training by sampling from linear interpolations of model inputs and their labels. While proven to be effective for computer vision (CV) and natural language processing (NLP) tasks, it remains unknown if mixup can bring performance improvement for DNNs developed for forecasting tasks.