Abstract: Imbalanced class distribution disrupts the training of a classifier, resulting in biases favoring majority classes. Data oversampling is a common strategy to tackle this issue. However, ...
Abstract: Lifelong learning (LLL) defines a training paradigm that aims to continuously acquire and capture new concepts from a sequence of tasks without forgetting. Recently, dynamic expansion models ...
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