update docs

Author: thucbx99

README.md

@@ -52,7 +52,7 @@ The currently supported algorithms include:
 
 ##### [Domain Generalization for Classification](/examples/domain_generalization/image_classification/)
 - [Two at Once: Enhancing Learning and Generalization Capacities via IBN-Net (IBN-Net, ECCV 2018)](https://openaccess.thecvf.com/content_ECCV_2018/papers/Xingang_Pan_Two_at_Once_ECCV_2018_paper.pdf)
-- [Domain Generalization with MixStyle (MixStyle, 2021 ICLR)](https://arxiv.org/abs/2104.02008)
+- [Domain Generalization with MixStyle (MixStyle, ICLR 2021)](https://arxiv.org/abs/2104.02008)
 - [Learning to Generalize: Meta-Learning for Domain Generalization (MLDG, AAAI 2018)](https://arxiv.org/pdf/1710.03463.pdf)
 - [Invariant Risk Minimization (IRM)](https://arxiv.org/abs/1907.02893)
 - [Out-of-Distribution Generalization via Risk Extrapolation (VREx, ICML 2021)](https://arxiv.org/abs/2003.00688)

examples/domain_adaptation/re_identification/README.md

@@ -60,6 +60,13 @@ If you use these methods in your research, please consider citing.
     year = {2018}  
 }
 
+@inproceedings{SPGAN,
+    title={Image-image domain adaptation with preserved self-similarity and domain-dissimilarity for person re-identification},
+    author={Deng, Weijian and Zheng, Liang and Ye, Qixiang and Kang, Guoliang and Yang, Yi and Jiao, Jianbin},
+    booktitle={CVPR},
+    year={2018}
+}
+
 @inproceedings{
     MMT,
     title={Mutual Mean-Teaching: Pseudo Label Refinery for Unsupervised Domain Adaptation on Person Re-identification},

examples/domain_generalization/image_classification/README.md

@@ -72,8 +72,8 @@ If you use these methods in your research, please consider citing.
 @inproceedings{MLDG,
     title={Learning to Generalize: Meta-Learning for Domain Generalization},
     author={Li, Da and Yang, Yongxin and Song, Yi-Zhe and Hospedales, Timothy},
-  	booktitle={AAAI Conference on Artificial Intelligence},
-  	year={2018}
+    booktitle={AAAI},
+    year={2018}
 }
  
 @misc{IRM,