Description : This package includes the python code of the DPONSS algorithm [1]. This is a distributed version of our previous PONSS algorithm [2] for the noisy subset selection problem. DPONSS uses a two-round divide and conquer strategy and can be easily implemented in the MapReduce framework. A Readme file and an example file are included in the package. In the 'example.sh', you will find an example of using this code for the application of sparse regression.

References: [1] Chao Qian. Distributed Pareto Optimization for Large-scale Noisy Subset Selection. IEEE Transactions on Evolutionary Computation, in press. [2] 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.

ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Dr. Chao Qian (qianc@lamda.nju.edu.cn).

Requirement: The package was developed with python.

Download: code (1MB)