Session area: Cybernetics

SPECIAL SESSION ON SPECIAL SESSION CODE: 5mxd3

Session description
The purpose of this special session is twofold, a) to highlight new research in sparse data analysis and representation, and b) to link outstanding studies in the fields of sparse data analysis and multi-agent system. Sparse data analysis effectively supports various real-world applications in bioinformatics, healthcare, social network services, finance prediction, intelligent transportation management, etc. It is well known that the performance of such analysis methods depends largely on the data representation applied. Representational learning, a common area of concern for all, is dedicated to learn meaningful and useful data representations best. Although representation learning is successfully applied to vision, audio and language processing, existing sparse data representation models suffer from insufficient modeling and optimization, overfitting and underfitting, lack of adaptability across diverse domains, and concealment of training and output processes. On the other hand, a multi-agent system provides an appropriate framework to support the development of advanced systems, where autonomous agents with predictive data analysis capabilities use the generated large-scale data to predict system objectives. A key to the success of a multi-agent system is an efficient and effective multi-agent algorithm. How to effectively analyze and accurately represent sparse data and improve the efficiency of multi-agent system is a thorny problem with great significance. This special session will provide a forum that brings together researchers and industry practitioners for the exchange of the latest theoretical developments in data analysis, representation learning, multi-agent system and the best practice for a wide range of applications.

Topics of interest include, but are not limited to:
(1) Latent Factor Analysis
(2) Latent Factorization of Tensors
(3) Sparse Tensor Networks
(4) Social Network Analysis
(5) Multi-agent Models
(6) Machine Learning for Multi-Agent Systems
(7) Evolutionary Computing-based Methods
(8) Deep Representation Learning
(9) Recommender Systems
(10) Intelligent Transportation Analysis
(11) Biomedical Informatics
(12) Healthcare Information System
(13) Multi-agent Coordination System

SUBMISSION
Papers must be submitted electronically for peer review through PaperCept by April 15, 2020: https://conf.papercept.net/conferences/scripts/start.pl In PaperCept, click on the SMC 2020 link “Submit a contribution to SMC2020” and click on the “Special Session Papers”.
All papers (6-8 pages) must be written in English and should describe original work. For guidelines, please follow the SMC website link http://smc2020.org/submission

DEADLINES
April 15, 2020: deadline for paper submission
May 24, 2020: notification of paper acceptance/rejection
July 22, 2020: deadline for final camera-ready papers

Session Organizers:
Prof. Xin LUO, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences
Prof. Long JIN, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences
Prof. Lun HU, Xinjiang Institute of Physics and Chemistry, Chinese Academy of Sciences
Dr. Pengwei HU, IBM Research