Abstract: Non-exemplar class-incremental learning refers to continual classifying of new and old classes without storing samples of old classes. Since only new class samples are available, ...
Abstract: In this paper, we analyze the effects of random sampling on adaptive diffusion networks. These networks consist in a collection of nodes that can measure and process data, and that can ...
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