Addressing the Devastating Effects of Single-Task Data Poisoning in Exemplar-Free Continual Learning

Our research addresses the overlooked security concerns related to data poisoning in continual learning CL. Data poisoning - the intentional manipulation of training data to affect the predictions of machine learning models - was recently shown to be a threat to CL training stability. While...