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• W2973877675 abstract "We describe a method for approximating any bounded activation function given encrypted input data. The utility of our method is exemplified by simulating it within two typical machine learning tasks: namely, a Variational Autoencoder that learns a latent representation of MNIST data, and an MNIST image classifier." @default.
• W2973877675 created "2019-09-26" @default.
• W2973877675 creator A5052428595 @default.
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• W2973877675 date "2019-05-01" @default.
• W2973877675 modified "2023-09-23" @default.
• W2973877675 title "Efficient Evaluation of Activation Functions over Encrypted Data" @default.
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• W2973877675 doi "https://doi.org/10.1109/spw.2019.00022" @default.
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