Sparse Optimization
Special Session in World Congress on Computational Intelligence 2018
http://www.ecomp.poli.br/~wcci2018/
Aim
According to compressed sensing theory, an unknown sparse or compressive signal can be recovered from a few measured values, which are much less than those used in previous theories such as Nyquist sampling theorem. Many single-objective sparse optimization algorithms have been proposed to solve the sparse optimization problems. However, the regulation parameter in single-objective sparse optimization problem is difficult to be set. Several multi-objective sparse optimization algorithms have been proposed to eliminate the regulation parameter, but the reconstruction accuracy is not satisfactory.
This special session aims to promote the design of novel algorithms to solving spare optimization problems.
Scope
Topics of interest may cover, but are not limited to
Evolutionary algorithms for sparse optimization
Evolutionary algorithms for sparse reconstruction
Encoding methods for sparse optimization
Evaluations of sparse optimization algorithms
Related theory analysis
Applications
Submissions
Papers should be submitted following the instructions at the IEEE WCCI 2018 web site. Please select the main research topic as the Special Session on "Sparse optimization”. Accepted papers will be included and published in the conference proceedings.
Deadline: 15th December 2017
Notification: 15th March 2018
Information on the format and templates for papers can be found here:
http://www.ecomp.poli.br/~wcci2018/submissions/#papersubmission
Matlab Codes of Sparse Optimization Test Functions are attached.
Organizers
Dr. Jing Liang
Professor, Zhengzhou University, Zhengzhou, China
liangjing@zzu.edu.cn
Dr. Maoguo Gong
Professor, Xidian University, Xian, China
gong@ieee.org
Dr. Hui Li
Associate professor, Xian Jiaotong University, Xian, China
lihui10@xjtu.edu.cn