Meta Weight Learning via Model-Agnostic Meta-Learning

Zhixiong Xu
Zhixiong Xu
Wei Tang
Wei Tang
Jun Lai
Jun Lai

Neurocomputing, 2020.

Cited by: 0|Views2

Abstract:

Abstract While meta learning approaches have achieved remarkable success, obtaining a stable and unbiased meta-learner remains a significant challenge, since the initial model of a meta-learner could be too biased towards existing tasks to adapt to new tasks. In order to avoid a biased meta-learner and improve its generalizability, this...More

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