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This paper proposes an efficient optimizer called AdaPlus which integratesNesterov momentum and precise stepsize adjustment on AdamW basis. AdaPluscombines the advantages of AdamW, Nadam, and AdaBelief and, in particular, doesnot introduce any extra hyper-parameters. We perform extensive experimentalevaluations on three machine learning tasks to validate the effectiveness ofAdaPlus. The experiment results validate that AdaPlus (i) among all theevaluated adaptive methods, performs most comparable with (even slightly betterthan) SGD with momentum on image classification tasks and (ii) outperformsother state-of-the-art optimizers on language modeling tasks and illustratespretty high stability when training GANs. The experiment code of AdaPlus willbe accessible at: https://github.com/guanleics/AdaPlus.

AdaPlus: Integrating Nesterov Momentum and Precise Stepsize Adjustment on AdamW Basis