BriefGPT.xyz
May, 2017
深度神经网络训练的有偏重要性采样
Biased Importance Sampling for Deep Neural Network Training
HTML
PDF
Angelos Katharopoulos, François Fleuret
TL;DR
本文提出一种有效的计算深度学习模型中loss value的方法,它使用小型模型在并行训练时提高了深度学习优化中重要抽样的应用。结果表明,此方法在测试深度卷积和递归神经网络的图像分类和语言建模任务时取得了良好的普适性。
Abstract
importance sampling
has been successfully used to accelerate
stochastic optimization
in many convex problems. However, the lack of an efficient way to calculate the importance still hinders its application to
→