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Anonymizing Sensor Data on the Edge: A Representation Learning and Transformation Approach
In the deterministic case, we use a linear transformation to move the representation of input data in the latent space such that the reconstructed data is likely to have the same public attribute but a different private attribute than the original input data.
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