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Distributed LSTM-Learning from Differentially Private Label Proportions
Data privacy and decentralised data collection has become more and more popular in recent years.
LOSDD: Leave-Out Support Vector Data Description for Outlier Detection
Support Vector Machines have been successfully used for one-class classification (OCSVM, SVDD) when trained on clean data, but they work much worse on dirty data: outliers present in the training data tend to become support vectors, and are hence considered "normal".
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