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arXiv · 2511.13465

AdamNX: An Adam improvement algorithm based on a novel exponential decay mechanism for the second-order moment estimate

Meng Zhu·Quan Xiao·Weidong Min
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Abstract

This paper studies the exponential decay mechanism of the second-moment estimate in Adam. We propose AdamNX and a time-varying second-moment decay rate that gradually weakens the correction applied to the update scale. Under the assumptions used in our analysis, this mechanism makes the updates approach momentum-SGD-like behavior during the training plateau phase. We report results on the image-classification, object-detection, and semantic-segmentation tasks, configurations, and comparators included in this paper. These results do not establish multi-seed statistical effects, flatness, or generalization beyond the reported tasks. Our code is open-sourced at https://github.com/mengzhu0308/AdamNX.

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Meng Zhu, Quan Xiao, Weidong Min. 2026-07-24. AdamNX: An Adam improvement algorithm based on a novel exponential decay mechanism for the second-order moment estimate. https://arxiv.org/abs/2511.13465

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