LEARNING DEVICE, LEARNING METHOD AND LEARNING PROGRAM
An acquisition unit acquires data for which a label is to be predicted. A learning unit learns a model representing a probability distribution of a label of the acquired data by using, as a filter, a correct answer label of the data so as to correctly predict a label for an adversarial example in which noise is added to the data.
1 . A learning apparatus comprising:
a memory; and
a processor coupled to the memory and programmed to execute a process comprising:
acquiring data for which a label is to be predicted; and
learning a model representing a probability distribution of a label of the acquired data by using, as a filter, a correct answer label of the data so as to correctly predict a label for an adversarial example in which noise is added to the data.
2 . The learning apparatus according to claim 1 , wherein the learning minimizes a probability distribution of a label of the data to a fixed value in a loss function for the adversarial example.
3 . The learning apparatus according to claim 1 , further comprising predicting a label of the acquired data by using the learned model.
4 . A learning method executed by a learning apparatus, the method comprising:
an acquisition step of acquiring data for which a label is to be predicted; and
a learning step of learning a model representing a probability distribution of a label of the acquired data by using, as a filter, a correct answer label of the data so as to correctly predict a label for an adversarial example in which noise is added to the data.
5 . A computer-readable recording medium having stored a learning program causing a computer to execute a process comprising:
an acquisition step of acquiring data for which a label is to be predicted; and
a learning step of learning a model representing a probability distribution of a label of the acquired data by using, as a filter, a correct answer label of the data so as to correctly predict a label for an adversarial example in which noise is added to the data.