In classification, semi-supervised learning occurs when a large amount of unlabeled data is available with only a small number of labeled data. In such a ...
In classification, semi-supervised learning occurs when a large amount of unlabeled data is avail- able with only a small number of labeled data.
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Large Margin Semi-supervised Learning. Junhui Wang and Xiaotong Shen. School of Statistics. University of Minnesota. Email: xshen@stat.umn.edu. Page 2. Overview.
This article develops a large margin semisuper- vised learning method, with most effort focused towards utilizing unlabeled data more efficiently to deliver ...
In classification, semisupervised learning usually involves a large amount of unlabeled data with only a small number of labeled data. This imposes a great ...
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Semi-supervised structured classification has been developed to handle large amounts of unlabelled structured data. In this work, we consider ...
In classification, semi-supervised learning occurs when a large amount of unlabeled data is avail- able with only a small number of labeled data.
To enhance predictability of classification, this article introduces a large margin semisupervised learning method constructing an efficient loss to measure the ...
Missing: Semi- supervised
In classification, semi-supervised learning occurs when a large amount of unlabeled data is available with only a small number of labeled data.
This article develops a large margin semisupervised learning method, which aims to extract the information from unlabeled data for estimating the Bayes decision ...