| Grant number: | 16/18615-0 |
| Support Opportunities: | Research Grants - Research Partnership for Technological Innovation - PITE |
| Start date: | September 01, 2017 |
| End date: | February 29, 2020 |
| Field of knowledge: | Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques |
| Agreement: | IBM Brasil |
| Principal Investigator: | André Carlos Ponce de Leon Ferreira de Carvalho |
| Grantee: | André Carlos Ponce de Leon Ferreira de Carvalho |
| Host Institution: | Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
| Company: | IBM Brasil - Indústria, Máquinas e Serviços Ltda |
| City: | São Carlos |
| Associated researchers: | Ana Carolina Lorena ; Gustavo Enrique de Almeida Prado Alves Batista ; Moacir Antonelli Ponti ; Paula Costa Castro ; Renato Tinós ; Ricardo Cerri |
Abstract
Without being aware, we are using technologies based on Machine learning (ML) algorithms in a growing number of our daily activities. The use of ML has made many risk and tiring activities safer, more reliable and more accurate. Despite these contributions, new demands require the development of new ML algorithms, or use of these algorithms in new and innovative ways. Two important current demands are to efficiently deal data that arrive in streams, where novelties can appear and concepts can change, and how to improve the use of the most appropriate ML algorithms, and the adequate values for the hyper-parameters of the algorithms selected for a new task. This project will investigate new approaches to efficiently deal with these demands. (AU)
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