Ján Čegiň

Position: Machine learning with human in the loop

Supervising team: Jakub Šimko (KInIT), Peter Brusilovsky (University of Pittsburgh)

Adversarial training is one of the methods to increase robustness of machine learning models used in false information detection. Increasing the diversity of adversarial examples is crucial in successful adversarial training, which is where human-in-the-loop methods come into play.

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