Name: Advanced Techniques in Optimization for Machine Learning and Imaging
SKU: 64792754
Price: 7118.00 TWD
Availability: InStock
Author: Alessandro Benfenati;Tatiana Alessandra Bubba;Marco Viola;Federica Porta
ISBN: 9789819767687

portada Advanced Techniques in Optimization for Machine Learning and Imaging

Advanced Techniques in Optimization for Machine Learning and Imaging

Type

Physical Book

Publisher

Springer Nature

Author

Alessandro Benfenati;Tatiana Alessandra Bubba;Marco Viola;Federica Porta

Collection

Springer INdAM Series

Year

2024

Pages

165

Format

Hardcover

Dimensions

23.5x15.5 cm

ISBN13

9789819767687

Advanced Techniques in Optimization for Machine Learning and Imaging

Alessandro Benfenati;Tatiana Alessandra Bubba;Marco Viola;Federica Porta (Author) · Springer Nature · Hardcover

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Synopsis "Advanced Techniques in Optimization for Machine Learning and Imaging"

In recent years, non-linear optimization has had a crucial role in the development of modern techniques at the interface of machine learning and imaging. The present book is a collection of recent contributions in the field of optimization, either revisiting consolidated ideas to provide formal theoretical guarantees or providing comparative numerical studies for challenging inverse problems in imaging. The work of these papers originated in the INdAM Workshop “Advanced Techniques in Optimization for Machine learning and Imaging” held in Roma, Italy, on June 20-24, 2022. The covered topics include non-smooth optimisation techniques for model-driven variational regularization, fixed-point continuation algorithms and their theoretical analysis for selection strategies of the regularization parameter for linear inverse problems in imaging, different perspectives on Support Vector Machines trained via Majorization-Minimization methods, generalization of Bayesian statistical frameworks to imaging problems, and creation of benchmark datasets for testing new methods and algorithms.