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We are concerned with a worst-case scenario in model generalization, in the sense that a model aims to perform well on many unseen domains while there is only one single domain available for training.
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AdaTransform: Adaptive data transformation
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Learning robust global representations by penalizing local predictive power
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d-sne: Domain adaptation using stochastic neighborhood embedding
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Maximum-entropy adversarial data augmentation for improved generalization and robustness
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