来源 | towardsdatascience
【导读】近日，两位Facebook的研究员小哥，提出了一种新的对比各种自监督学习框架的方法，结果显示SimCLR、CPC、AMDIM这些框架，彼此之间并无本质差异。
对比自监督学习将取代监督式深度学习主导地位的预言，已经「甚嚣尘上」。
Hinton大力推广的SimCLR就是其中一种。
对比自监督学习（CLS）是从无标签数据中选择和对比Anchor，Positive，Negative（APN）三种特征，学习到有用表征的方法。
近日，Facebook的两位研究员，使用一个新的框架来对比分析了目前三个主流的自监督学习算法：SimCLR、CPC、AMDIM。结果显示，尽管这些方法表面上看起来非常不同，但实际上他们互相之间只有微小的差异。
回顾：自监督学习和对比学习
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本篇文章来源于: 深度学习这件小事
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