Removing bias for out-of-distribution generalization
Deep models have a strong ability to fit the training data, and thus can achieve high performance when the testing data is sampled from the same distribution as the training. However, in practice, the deep models fail to perform perfectly because the testing data is usually Out-of-Distribution (OOD)...
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Format: | Thesis-Doctor of Philosophy |
Language: | English |
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Nanyang Technological University
2023
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Online Access: | https://hdl.handle.net/10356/168654 |
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Institution: | Nanyang Technological University |
Language: | English |