Learning feed-forward one-shot learners

Luca Bertinetto, João F. Henriques, Jack Valmadre, Philip Torr, Andrea Vedaldi

Neural Information Processing Systems 

In this manner we obtain an efficient feed-forward one-shot learner, trained end-to-end by minimizing a one-shot classification objective in a learning to learn formulation. In order to make the construction feasible, we propose a number of factorizations of the parameters of the pupil network.

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