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Nov, 2022
零偏差标量不变网络
Scalar Invariant Networks with Zero Bias
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Chuqin Geng, Xiaojie Xu, Haolin Ye, Xujie Si
TL;DR
本文研究讨论在解决图像分类相关任务时,通过考虑输入空间的内在分布和模型的首要属性,可以忽略偏差对神经网络效果的影响,而使用零偏差神经网络可能在保持同等性能下,拥有更好的标量不变性和学习图像的能力,在低光照条件下通过只乘以0.01的标量来预测的情况下,其性能显著高于现有的基准模型(超过60%)。
Abstract
Just like weights, bias terms are the learnable parameters of many popular machine learning models, including
neural networks
.
biases
are believed to effectively increase the representational power of
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