[Research] Deep Critical Learning (i.e., Deep Robustness) In The Era of Big Data

Here are related papers on the fitting and generalization of deep learning:
* [ProSelfLC: Progressive Self Label Correction Towards A Low-Temperature Entropy State](https://arxiv.org/abs/2207.00118)
* [Understanding deep learning requires rethinking generalization](https://arxiv.org/abs/1611.03530)
* [A Closer Look at Memorization in Deep Networks](https://arxiv.org/abs/1706.05394)
* [ProSelfLC: Progressive Self Label Correction for Training Robust Deep Neural Networks](https://arxiv.org/abs/2005.03788)
* Blog link: [https://xinshaoamoswang.github.io/blogs/2020-06-07-Progressive-self-label-correction/](https://xinshaoamoswang.github.io/blogs/2020-06-07-Progressive-self-label-correction/)
* [Mean Absolute Error Does Not Treat Examples Equally and Gradient Magnitude’s Variance Matters](https://github.com/XinshaoAmosWang/Improving-Mean-Absolute-Error-against-CCE)
* [Derivative Manipulation: Example Weighting via Emphasis Density Funtion in the …

big big data data learning machinelearning research robustness