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Budget Semi-supervised Learning
2009In this paper we propose to study budget semi-supervised learning , i.e., semi-supervised learning with a resource budget, such as a limited memory insufficient to accommodate and/or process all available unlabeled data. This setting is with practical importance because in most real scenarios although there may exist abundant unlabeled data, the ...
Qiao-Qiao She +3 more
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Semi-supervised learning in knowledge discovery
Fuzzy Sets and Systems, 2005zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Aljoscha Klose, Rudolf Kruse
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Semi-supervised Learning with Transfer Learning
2013Traditional machine learning works well under the assumption that the training data and test data are in the same distribution. However, in many real-world applications, this assumption does not hold. The research of knowledge transfer has received considerable interest recently in Natural Language Processing to improve the domain adaptation of machine
Huiwei Zhou +3 more
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Multiview Semi-supervised Learning
2019Semi-supervised learning is concerned with such learning scenarios where only a small portion of training data are labeled. In multiview settings, unlabeled data can be used to regularize the prediction functions, and thus to reduce the search space. In this chapter, we introduce two categories of multiview semi-supervised learning methods.
Lidan Wu +3 more
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Introduction to Semi-Supervised Learning
Synthesis Lectures on Artificial Intelligence and Machine Learning, 2009Xiaojin Zhu, A. Goldberg
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Deep semi-supervised learning for medical image segmentation: A review
Expert systems with applicationsKai Han +6 more
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