Nonchalant
发表于 2025-3-21 19:11:20
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Flirtatious
发表于 2025-3-21 21:36:53
,Motivation and Overview of Normalization in DNNs,een examples will be dominated by these dimensions, which will impair the performance of the learner. Besides, normalizing an input can improve the optimization efficiency for parametric models. There exist theoretical advantages to normalization for linear models, as we will illustrate.
Blatant
发表于 2025-3-22 03:11:20
,A General View of Normalizing Activations,oduce the preliminary work of normalizing activations of DNNs, prior to the milestone normalization technique—batch normalization (BN) [.]. We then illustrate the algorithm of BN and how it is developed by exploiting the merits of the previous methods.
bleach
发表于 2025-3-22 07:07:09
,BN for More Robust Estimation,ng along the batch dimension, as introduced in previous sections. Here, we will discuss the more robust estimation methods that also address this problem of BN. One way to reduce the discrepancy between training and inference is to combine the estimated population statistics for normalization during training.
语言学
发表于 2025-3-22 11:57:51
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ASSAY
发表于 2025-3-22 15:30:38
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过于平凡
发表于 2025-3-22 20:25:14
,Summary and Discussion,le to design new normalization methods tailored to specific tasks (by the choice of NAP) or improve the trade-off between efficiency and performance (by the choice of NOP). We leave the following open problems for discussion.
AVANT
发表于 2025-3-22 21:12:50
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词汇表
发表于 2025-3-23 01:41:08
,Multi-mode and Combinational Normalization, GMM distribution as: . where . represents .-th Gaussian in the mixture model .. It is possible to estimate the mixture coefficient . and further derive the soft-assignment mechanism ., by using the expectation-maximization (EM) [.] algorithm.
轨道
发表于 2025-3-23 07:56:56
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