Distributed optimization algorithms for Big Data
Anno
2017
Proponente Francisco Facchinei - Professore Ordinario
Sottosettore ERC del proponente del progetto
Componenti gruppo di ricerca
| Componente | Categoria |
|---|---|
| Laura Palagi | Componenti il gruppo di ricerca |
| Simone Sagratella | Dottorando/Assegnista/Specializzando componente il gruppo di ricerca |
| Antonio Sassano | Componenti il gruppo di ricerca |
Abstract
The continuous, pervasive collection of enormous amounts of data and the advances in computational power present major challenges to modern big data analytics. Modeling and processing these huge data sets require the solution of hard optimization problems with features that include huge dimensionality, high non convexity and/or non differentiability of the functions involved.
To address such challenges, this project aims at analyzing new algorithmic frameworks enabling the parallel, distributed, and asynchronous solution of hard nonconvex and possibly nondifferentiable optimization problems.
ERC
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