Adaptive Online Learning for Gradient-Based Optimizers

1 Jun 2019Saeed MasoudianAli ArabzadehMahdi Jafari SiavoshaniMilad JalalAlireza Amouzad

As application demands for online convex optimization accelerate, the need for designing new methods that simultaneously cover a large class of convex functions and impose the lowest possible regret is highly rising. Known online optimization methods usually perform well only in specific settings, and their performance depends highly on the geometry of the decision space and cost functions... (read more)

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