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Stochastic gradient descent
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===Sign-based stochastic gradient descent=== Even though sign-based optimization goes back to the aforementioned ''Rprop'', in 2018 researchers tried to simplify Adam by removing the magnitude of the stochastic gradient from being taken into account and only considering its sign.<ref>{{cite web | url=https://openreview.net/forum?id=S1EwLkW0W | title=Dissecting Adam: The Sign, Magnitude and Variance of Stochastic Gradients | date=15 February 2018 | last1=Balles | first1=Lukas | last2=Hennig | first2=Philipp }}</ref><ref>{{cite web | url=https://proceedings.mlr.press/v80/bernstein18a.html | title=SignSGD: Compressed Optimisation for Non-Convex Problems | date=3 July 2018 | pages=560β569 }}</ref> {{expand section|date=June 2023}}<!--https://arxiv.org/pdf/2305.14342.pdf has more literature-->
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