Network-based Learning for High-Level Classification of Sequential Data

• Grant number: 24/02783-7
• Support Opportunities: Research Grants - Visiting Researcher Grant - Brazil
• Start date: April 01, 2024
• End date: March 31, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Zhao Liang
• Grantee: Zhao Liang
• Visiting researcher: Murillo Guimaraes Carneiro
• Visiting researcher institution: Faculdade De Computação/Facom/Ufu, Brazil
• Host Institution: Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto (FFCLRP). Universidade de São Paulo (USP). Ribeirão Preto , SP, Brazil
• Associated research grant: 19/07665-4 - Center for Artificial Intelligence, AP.eScience.CPE

Abstract

In this project we investigate techniques and heuristics based on complex networks and neural networks for data classification tasks. To be specific, the main goals are the development of network-based learning architectures for high-level classification as well as the application of such models for two sequential data classification problems related to the analysis of EEG signals and the classification of infrared spectroscopy data. As a result, we expect that the approaches developed will take advantage of structural and dynamical properties of the input data in order to improve the predictive performance of traditional techniques, especially considering healthcare applications such as the prognosis of patients in coma and the detection of oral cancer. (AU)