Update README.md

README.md

@@ -9,6 +9,30 @@ tags:
   - transformers
 ---
 
-**Paper title here**
+**Privacy-Preserving Split Learning via Patch Shuffling over Transformers**
 
-Paper: https://ieeexplore.ieee.org/abstract/document/10027647
+Paper: https://ieeexplore.ieee.org/abstract/document/10027647
+ 
+## API of Patch Shuffling
+### PatchShuffle
+function: ```utilsenc.PatchShuffle(x)->y```  
+x: input feature; y: outputfeature
+### BatchShuffle  
+function: ```utilsenc.BatchPatchPartialShuffle(x,k1)->y```  
+x: input feature; k: proportions of patches not to be shuffle; y: outputfeature
+### SpectralShuffle
+The function is the same as PatchShuffle or BatchShuffle, but first turn models into spectral domain. Please see the example as reference.
+
+**Citation**
+Bibtex
+```
+@INPROCEEDINGS{patchshuffling,
+  author={Yao, Dixi and Xiang, Liyao and Xu, Hengyuan and Ye, Hangyu and Chen, Yingqi},
+  booktitle={2022 IEEE International Conference on Data Mining (ICDM)}, 
+  title={Privacy-Preserving Split Learning via Patch Shuffling over Transformers}, 
+  year={2022},
+  pages={638-647},
+  doi={10.1109/ICDM54844.2022.00074}
+}
+```
+D. Yao, L. Xiang, H. Xu, H. Ye and Y. Chen, "Privacy-Preserving Split Learning via Patch Shuffling over Transformers," 2022 IEEE International Conference on Data Mining (ICDM), Orlando, FL, USA, 2022, pp. 638-647, doi: 10.1109/ICDM54844.2022.00074.