For years, the guiding assumption of artificial intelligence has been simple: an AI is only as good as the data it has seen. Feed it more, train it longer, and it performs better. Feed it less, and it ...
Abstract: Class Incremental Learning (CIL) aims to enable models to learn new classes sequentially while retaining knowledge of previous ones. Although current methods have alleviated catastrophic ...
Abstract: Unsupervised feature selection plays a crucial role in dealing with unlabeled high-dimensional data. However, traditional unsupervised feature selection methods have some limitations. They ...
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