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                   Readme for the CRIA Package
 		       version July 2020

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The package includes the CRIA algoirthms implemented in [1] for multi-label crowdsourcing learning with incomplete annotations.

[1] S.-Y. Li and Y. Jiang. Multi-label Crowdsourcing Learning with Incomplete Annotations. In 15th Pacific Rim International Conference on Artificial Intelligence, 232-245, 2018.

ATTN:

• This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Professor Zhi-Hua Zhou(zhouzh@nju.edu.cn).

• This package was developed by Ms. Shao-Yuan Li (lisy@nuaa.edu.cn). For any problem concerning the code, please feel free to contact Ms. Li.

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Code description: CRIA.rar: The multi-label crowdsourcing with incomplete annotation algorithm. To get demo results, run CRIA/main.m in matlab.

data_sample.rar: one dataset sample used in [1], corresponds to the Scene [1].

misc.rar: resource functions used by the algorithm