OvA-INN: Continual Learning with Invertible Neural Networks

ICLR 2020 G. HocquetO. BichlerD. Querlioz

In the field of Continual Learning, the objective is to learn several tasks one after the other without access to the data from previous tasks. Several solutions have been proposed to tackle this problem but they usually assume that the user knows which of the tasks to perform at test time on a particular sample, or rely on small samples from previous data and most of them suffer of a substantial drop in accuracy when updated with batches of only one class at a time... (read more)

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