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Edge dynamics in complex networks for data classification

Grant number: 15/18456-6
Support type:Scholarships abroad - Research Internship - Doctorate (Direct)
Effective date (Start): February 01, 2016
Effective date (End): January 29, 2017
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal researcher:Zhao Liang
Grantee:Filipe Alves Neto Verri
Supervisor abroad: Ying-Cheng Lai
Home Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Research place: Arizona State University, Tempe (ASU), United States  
Associated to the scholarship:13/25876-6 - High level data classification based on complex network applied to invariant pattern recognition, BP.DD

Abstract

Complex networks are graphs that model natural systems with nontrivial topology and dynamics. The topological properties and the evolution of these networks give information about the systems that they represent. This theory may be applied to solve machine learning tasks such as data classification. One example of dynamical learning mechanism in complex networks is the particle competition. Recently, an alternative particle competition scheme emphasizing the edge dynamics was proposed. This approach, called Edge Domination System, offers better understanding of the system behavior than the vertex dynamics. The objectives of the regular fellowship are developing, analyzing, and applying data classification techniques based on dynamical systems in complex networks. The internship abroad intends to enhance the mathematical background that is fundamental to investigate such systems. This research plan proposes to study, analyze and model dynamical systems emphasizing edge dynamics for data classification problems. (AU)

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Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
NETO VERRI, FILIPE ALVES; URIO, PAULO ROBERTO; ZHAO, LIANG. Network Unfolding Map by Vertex-Edge Dynamics Modeling. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, v. 29, n. 2, p. 405-418, . (15/18456-6, 13/07375-0, 11/50151-0, 13/25876-6)

Please report errors in scientific publications list by writing to: cdi@fapesp.br.