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Privacy advocates want deep learning systems to forget what they’ve learned. What’s new: Researchers are seeking ways to remove the influence of particular training examples, such as an individual’s personal information, from a trained model without affecting its performance, Wired reported.
Privacy advocates want deep learning systems to forget what they’ve learned. What’s new: Researchers are seeking ways to remove the influence of particular training examples, such as an individual’s personal information, from a trained model without affecting its performance, Wired reported.
With access to a trained model, an attacker can use a reconstruction attack to approximate its training data. A method called InstaHide recently won acclaim for promising to make such examples unrecognizable to human eyes while retaining their utility for training.
With access to a trained model, an attacker can use a reconstruction attack to approximate its training data. A method called InstaHide recently won acclaim for promising to make such examples unrecognizable to human eyes while retaining their utility for training.
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