Decoupling "when to update" from "how to update"

Authors: eran malach, Shai Shalev-Shwartz

Abstract

Deep learning requires data. A useful approach to obtain data is to be creative and mine data from various sources, that were created for different purposes. Unfortunately, this approach often leads to noisy labels. In this paper, we propose a meta algorithm for tackling the noisy labels problem. The key idea is to decouple

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