Web: http://arxiv.org/abs/2205.05831

May 13, 2022, 1:11 a.m. | Hongyu Wang, Eibe Frank, Bernhard Pfahringer, Michael Mayo, Geoffrey Holmes

cs.LG updates on arXiv.org arxiv.org

Cross-domain few-shot meta-learning (CDFSML) addresses learning problems
where knowledge needs to be transferred from several source domains into an
instance-scarce target domain with an explicitly different input distribution.
Recently published CDFSML methods generally construct a "universal model" that
combines knowledge of multiple source domains into one backbone feature
extractor. This enables efficient inference but necessitates re-computation of
the backbone whenever a new source domain is added. Moreover, state-of-the-art
methods derive their universal model from a collection of backbones -- normally …

arxiv cross cv learning meta meta-learning

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