This article aims to introduce a new kind of framework in contrastive learning which does not use negative samples.

Paper: Chen, X., & He, K. (2021). Exploring simple siamese representation learning. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 15750-15758). Updated version accessed at: https://arxiv.org/abs/2011.10566

This article decribes a milestone in contrastive learning and the best paper Nominee in CVPR 2020.

Paper: He, K., Fan, H., Wu, Y., Xie, S., and Girshick, R. Momentum contrast for unsupervised visual representation learning. arXiv preprint arXiv:1911.05722, 2019. Updated version accessed at: https://arxiv.org/abs/1911.05722.

This article decribes an end-to-end framework for contrastive learning called SimCLR.

Paper: Ting Chen, Simon Kornblith, Mohammad Norouzi, and Ge- offrey Hinton. A simple framework for contrastive learning of visual representations. arXiv:2002.05709, 2020. Updated version accessed at: https://arxiv.org/abs/2002.05709.

UQ 2020 Semester 1 DATA7202 Statistical Methods for Data Science

多元线性回归复习笔记（不一定对），省略了很多证明，我能咋办，我也看不懂呀

好文：

https://zhuanlan.zhihu.com/p/25436791

https://www.cnblogs.com/nxld/p/6435677.html

https://zhuanlan.zhihu.com/p/48541799（几乎所有数学证明可以找到）