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The Global Landscape of Neural Networks: An Overview
IEEE Signal Processing Magazine ( IF 14.9 ) Pub Date : 2020-09-01 , DOI: 10.1109/msp.2020.3004124
Ruoyu Sun , Dawei Li , Shiyu Liang , Tian Ding , Rayadurgam Srikant

One of the major concerns for neural network training is that the nonconvexity of the associated loss functions may cause a bad landscape. The recent success of neural networks suggests that their loss landscape is not too bad, but what specific results do we know about the landscape? In this article, we review recent findings and results on the global landscape of neural networks.

中文翻译:

神经网络的全球格局:概述

神经网络训练的主要问题之一是相关损失函数的非凸性可能会导致糟糕的景观。神经网络最近的成功表明它们的损失情况还不错,但是我们对这种情况了解哪些具体结果?在本文中,我们回顾了有关神经网络全球格局的最新发现和结果。
更新日期:2020-09-01
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