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4 produkter
4 produkter
1 387 kr
Skickas inom 10-15 vardagar
This volume brings together new papers advancing contemporary debates in foundational, conceptual, and methodological issues in cognitive neuroscience.
1 387 kr
Skickas inom 10-15 vardagar
This volume brings together new papers advancing contemporary debates in foundational, conceptual, and methodological issues in cognitive neuroscience.
Del 61 - Springer INdAM Series
Advanced Techniques in Optimization for Machine Learning and Imaging
Inbunden, Engelska, 2024
2 320 kr
Skickas inom 10-15 vardagar
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.
Del 61 - Springer INdAM Series
Advanced Techniques in Optimization for Machine Learning and Imaging
Häftad, Engelska, 2025
2 320 kr
Skickas inom 10-15 vardagar
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.