郑州大学计算智能实验室

Computational Intelligence Laboratory

Call for Papers in Special Session in WCCI2018

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