Abstract: A method of unlearning a training example from a neural network, comprising: during training of the neural network on a training dataset, recording a plurality of recordings in a recording dataset, wherein a recording includes weight values of the neural network at the time at which the recording is recorded, selecting an unlearning training example to unlearn from the neural network, computing a total-loss value of a change in a loss function for each of plurality of training examples induced by a change of weights of the neural network in response to the unlearning training example, determining a certain recording to use to remove the unlearning training example according to the total-loss values, and re-training the neural network from the determined certain recording using an adapted training dataset excluding the unlearning training example; and producing an unlearned neural network.

Abstract: A method of unlearning a training example from a neural network, comprising: during training of the neural network on a training dataset, recording a plurality of recordings in a recording dataset, wherein a recording includes weight values of the neural network at the time at which the recording is recorded, selecting an unlearning training example to unlearn from the neural network, computing a total-loss value of a change in a loss function for each of plurality of training examples induced by a change of weights of the neural network in response to the unlearning training example, determining a certain recording to use to remove the unlearning training example according to the total-loss values, and re-training the neural network from the determined certain recording using an adapted training dataset excluding the unlearning training example; and producing an unlearned neural network.