Description: This package includes the JAVA code of the PONSS algorithm [1] for solving the noisy subset selection problem. Compared with the POSS algorithm [2] for noise-free subset selection, PONSS employs a noise-aware strategy in comparing solutions, which leads to a better performance. A Readme file and an example file are included in the package. In the 'Example.java', you will find an example of using this code for the application of influence maximization on the ego-facebook data set.
Reference:
[1] Chao Qian, Jing-Cheng Shi, Yang Yu, Ke Tang, and Zhi-Hua Zhou. Subset Selection under Noise. In: Advances in Neural Information Processing Systems 30 (NIPS'17), Long Beach, CA, 2017.
[2] Chao Qian, Yang Yu, and Zhi-Hua Zhou. Subset Selection by Pareto Optimization. In: Advances in Neural Information Processing Systems 28 (NIPS'15), Montreal, Canada, 2015.
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 (zhouzh@nju.edu.cn).
Requirement: The package was developed with JAVA.
ATTN2: This package was developed by Mr. Jing-Cheng Shi (shijc@lamda.nju.edu.cn). For any problem concerning the code, please feel free to contact Mr. Shi.
Download:
code (320KB)