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Numerical methods for computational and data science
The research group in numerical methods for computational and data science merges together analytical approaches and numerical techniques to address the solution of optimization problems arising in real-world applications.
Specific fields are:
Nonsmooth and nonconvex optimization
- Optimization and big data
- First order methods
- High performance computing
Numerical methods for image processing and machine learning
- Imaging and inverse problems
- Machine learning techniques
- Applications in medicine, engineering and astronomy
Staff researchers:
Silvia Bonettini, Federica Porta, Marco Prato, Simone Rebegoldi , Luca Zanni
[Ultimo aggiornamento: 04/02/2021 12:49:13]