A latent-noise autoencoder is claimed to reduce the biometric identifiability of gaze signals while preserving utility for gaze prediction and physiological plausibility of the output.
Differentially private recommender framework with dual semi-autoencoder
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Privacy Enhancement for Gaze Data Using a Noise-Infused Autoencoder
A latent-noise autoencoder is claimed to reduce the biometric identifiability of gaze signals while preserving utility for gaze prediction and physiological plausibility of the output.