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Models and algorithm for never-ending learning

Grant number: 13/07787-6
Support Opportunities:Regular Research Grants
Start date: July 01, 2013
End date: June 30, 2015
Field of knowledge:Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
Principal Investigator:Estevam Rafael Hruschka Júnior
Grantee:Estevam Rafael Hruschka Júnior
Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
Associated researchers: Thomas Michael Mitchell

Abstract

Machine Learning research has evolved and achieved important results in the last decades. We still don't have, however, a machine learning system capable of performing an autonomous and continuous learning, that can used the knowledge acquired yesterday to enhance its ability to learn better today. The first (and, to our knowledge, the only) never-ending learning system is named NELL (Never-Ending Language Learner). NELL has been developed at Carnegie Mellon University (CMU) in a joint effort with Federal University of Sao Carlos (UFSCar). The main goal of the research work proposed in this project is to keep on the investigation of the never-ending learning topic, and in addition, to propose and implement methods and algorithms to be coupled to never-ending learning systems. (AU)

Articles published in Agência FAPESP Newsletter about the research grant:
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Articles published in other media outlets ( ):
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VEICULO: TITULO (DATA)

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)
DO AMARAL, LAURENCE RODRIGUES; DA SILVA ALVES, ALEXANDRE HENRICK; MENDES, RAPHAEL DE LIMA; GOMES, MATHEUS DE SOUZA; LIMA BERTARINI, PEDRO LUIZ; HRUSCHKA JR, ESTEVAM RAFAEL; IEEE. Applying Never-Ending Learning (NEL) Principles to Build a Gene Ontology (GO) Biocurator. 2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), v. N/A, p. 8-pg., . (13/07787-6)
DA SILVA, NADIA F. F.; HRUSCHKA, EDUARDO R.; HRUSCHKA, JR., ESTEVAM R.. Tweet sentiment analysis with classifier ensembles. DECISION SUPPORT SYSTEMS, v. 66, p. 170-179, . (13/07375-0, 13/07787-6)
DO AMARAL, LAURENCE RODRIGUES; HRUSCHKA, JR., ESTEVAM RAFAEL. Transgenic: An evolutionary algorithm operator. Neurocomputing, v. 127, p. 104-113, . (13/07787-6)