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This paper studies a specific one-class classification problem where the training data are corrupted by significant outliers. Specifically, we are interested in the one-class support vector machine (OCSVM) approach that normally requires good training data. However, perfect training data are usually hard to obtain in most real-world applications due to the inherent data variability and uncertainty...
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