Domain adaptation via incremental confidence samples into classification
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DOI: 10.1002/int.22629
Abstract: To accurately recognize similar objects in different domains, the key for domain adaptation is to learn new metrics so as to minimize the discrepancy of two domains. Recent works utilize joint probability domain adaptation to… read more here.
Keywords: confidence samples; incremental confidence; samples classification; domain adaptation ... See more keywords
MutexMatch: Semi-supervised Learning with Mutex-based Consistency Regularization
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3228380
Abstract: The core issue in semi-supervised learning (SSL) lies in how to effectively leverage unlabeled data, whereas most existing methods tend to put a great emphasis on the utilization of high-confidence samples yet seldom fully explore… read more here.
Keywords: consistency; confidence; semi supervised; supervised learning ... See more keywords