Domain invariant representation learning with domain density transformations
Domain generalization refers to the problem where we aim to train a model on data from a set of source domains so that the model can generalize to unseen target domains. Naively training a model on the aggregate set of data (pooled from all source domains) has been shown to perform suboptimally, sin...
| Главные авторы: | , , , |
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| Формат: | Internet publication |
| Язык: | English |
| Опубликовано: |
arXiv
2021
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