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Convex optimization and extensions applied in Data Science

Grant number: 22/00380-7
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): September 01, 2022
Effective date (End): March 31, 2024
Field of knowledge:Physical Sciences and Mathematics - Mathematics - Applied Mathematics
Principal researcher:Paulo José da Silva e Silva
Grantee:Somayeh Khezri
Home Institution: Instituto de Matemática, Estatística e Computação Científica (IMECC). Universidade Estadual de Campinas (UNICAMP). Campinas , SP, Brazil
Associated research grant:18/24293-0 - Computational methods in optimization, AP.TEM

Abstract

Data Science problems have attracted tremendous interest in recent years due to society's unprecedented ability to gather data thatmust be processed.In this context, there has been a resurgence of convex optimization techniques and their extensions, which have been proven to be essential for training of the machine learning models that are fundamental in modern Artificial Intelligence (AI).This project seeks to investigate the use of modern convex optimization techniques in problems in the field of Data Science and Machine Learning such as learning from noisy data or using decomposition methods to induce parallelism or to decouple the problem allowing its solution

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