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Jun Kataoka – ProQuest LLC, 2024
This dissertation proposes novel Domain Adaptation (DA) methods in real-world industrial settings, where the availability of labeled data is limited and test data can significantly differ from training data. Particularly, our research addresses key challenges in DA, including the applicability of DA methods in industrial settings, strategies to…
Descriptors: Industry, Authentic Learning, Data, Training Methods