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data_augmentation [2018/06/04 17:10]
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data_augmentation [2018/06/04 22:14] (current)
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 Only using training data from the source domain, we propose an iterative procedure that augments the dataset with examples from a fictitious target domain that is "​hard"​ under the current model. We show that our iterative scheme is an adaptive data augmentation method where we append adversarial examples at each iteration. Only using training data from the source domain, we propose an iterative procedure that augments the dataset with examples from a fictitious target domain that is "​hard"​ under the current model. We show that our iterative scheme is an adaptive data augmentation method where we append adversarial examples at each iteration.
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 +https://​ai.googleblog.com/​2018/​06/​improving-deep-learning-performance.html ​