Description: The package includes the python code of the NACH algorithm for Robust Semi-Supervised Learning when Not All Classes have Labels.
[1].
References:
[1] Lan-Zhe Guo∗, Yi-Ge Zhang∗, Zhi-Fan Wu, Jie-Jing Shao, Yu-Feng Li. Robust Semi-Supervised Learning when Not All Classes have Labels. In: Advances in Neural Information Processing Systems 35 (NeurIPS 2022), New Orleans, LA, 2022.
ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact
Prof. Zhi-Hua Zhou.
ATTN2: This package was developed by
Mr. Lan-Zhe Guo,
Mr. Yi-Ge Zhang ，
Mr. Zhi-Fan Wu,
Mr.Jie-Jing Shao and
Mr.Yu-Feng Li. For any problem concerning the code, please feel free to contact any of the authors.
Requirement: The package was developed with Python.
Download: [
code] (406.00MB)