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cs.LG2023
Distributed LSTM-Learning from Differentially Private Label Proportions
Timon Sachweh, Daniel Boiar, Thomas Liebig
Data privacy and decentralised data collection has become more and more popular in recent years. In order to solve issues with privacy, communication bandwidth and learning from sp…
cs.LG2022
LOSDD: Leave-Out Support Vector Data Description for Outlier Detection
Daniel Boiar, Thomas Liebig, Erich Schubert
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…