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09/08/2023
Robust Representation Learning for Privacy-Preserving Machine Learning: A Multi-Objective Autoencoder Approach
Several domains increasingly rely on machine learning in their applicati...
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06/05/2023
A Privacy-Preserving Federated Learning Approach for Kernel methods
It is challenging to implement Kernel methods, if the data sources are d...
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02/07/2022
CECILIA: Comprehensive Secure Machine Learning Framework
Since machine learning algorithms have proven their success in data mini...
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02/17/2021
ppAUC: Privacy Preserving Area Under the Curve with Secure 3-Party Computation
Computing an AUC as a performance measure to compare the quality of diff...
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12/04/2020
ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare
To train sophisticated machine learning models one usually needs many tr...
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11/06/2019
