论文标题
在自我监督的代表性学习方面做出良好的实践
Towards Good Practices in Self-supervised Representation Learning
论文作者
论文摘要
在过去的几年中，自我监督的表示学习取得了显着的进步。最近，与其监督的学习对手相比，对比实例学习显示出令人印象深刻的结果。但是，即使对对比实例学习的兴趣不断增加，仍然不清楚为什么这些方法如此效果如此。在本文中，我们旨在揭开其成功背后的一些奥秘，这是好的做法。通过广泛的经验分析，我们希望不仅提供见解，而且希望提供一系列最佳实践，从而在自我监督的代表学习中取得了成功。
Self-supervised representation learning has seen remarkable progress in the last few years. More recently, contrastive instance learning has shown impressive results compared to its supervised learning counterparts. However, even with the ever increased interest in contrastive instance learning, it is still largely unclear why these methods work so well. In this paper, we aim to unravel some of the mysteries behind their success, which are the good practices. Through an extensive empirical analysis, we hope to not only provide insights but also lay out a set of best practices that led to the success of recent work in self-supervised representation learning.
