We describe and analyze a new boosting algorithm for deep learning called SelfieBoost. Unlike other boosting algorithms, like AdaBoost, which construct ensembles of classifiers, SelfieBoost boosts the accuracy of a single network. We prove a log(1/ ) convergence rate for SelfieBoost under some "SGD success" assumption which seems to hold in practice.
REF proposes a selfieBoost which boosts the accuracy of a single network.
SelfieBoost: A Boosting Algorithm for Deep Learning
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Computer Science Mathematics