Elastic Consistency

Dan Alistarh, I. Markov, Giorgi Nadiradze
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Abstract

Machine learning models can match or surpass humans on specialized tasks such as image classification [20, 14], speech recognition [37], or complex games [39]. One key tool behind this progress has been a family of optimization methods which fall under the umbrella term of stochastic gradient descent (SGD) [35], which are by and large the method of choice for training large-scale machine learning models.
弹性的一致性
机器学习模型可以在图像分类[20,14]、语音识别[37]或复杂游戏[39]等专业任务上匹配或超越人类。这一进展背后的一个关键工具是一系列优化方法,它们属于随机梯度下降(SGD)的总称[35],总的来说,这些方法是训练大规模机器学习模型的首选方法。
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