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Machine learning techniques may suffer from adversarial attack in which an attacker misleads a learning process by manipulating training samples. Data sanitization is one of countermeasures against poisoning attack. It is a data pre-processing method which filters suspect samples before learning. Recently, a number of data sanitization methods are devised for label flip attack, but their flexibility...
Poisoning attack in which an adversary misleads the learning process by manipulating its training set significantly affect the performance of classifiers in security applications. This paper proposed a robust learning method which reduces the influences of attack samples on learning. The sensitivity, defined as the fluctuation of the output with small perturbation of the input, in Localized Generalization...
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