iCaRL: Incremental Classifier and Representation Learning

CVPR 2017 Sylvestre-Alvise RebuffiAlexander KolesnikovGeorg SperlChristoph H. Lampert

A major open problem on the road to artificial intelligence is the development of incrementally learning systems that learn about more and more concepts over time from a stream of data. In this work, we introduce a new training strategy, iCaRL, that allows learning in such a class-incremental way: only the training data for a small number of classes has to be present at the same time and new classes can be added progressively... (read more)

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