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Advanced Techniques in Optimization for Machine Learning and Imaging
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7005607Advanced Techniques in Optimization for Machine Learning and Imaginghttps://www.gandhi.com.mx/advanced-techniques-in-optimization-for-machine-learning-and-imaging-9789819767694/phttps://gandhi.vtexassets.com/arquivos/ids/6545553/image.jpg?v=63863554227157000033173686MXNSpringer Nature SingaporeInStock/Ebooks/<p>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.</p><p>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.</p>...6677298Advanced Techniques in Optimization for Machine Learning and Imaging33173686https://www.gandhi.com.mx/advanced-techniques-in-optimization-for-machine-learning-and-imaging-9789819767694/phttps://gandhi.vtexassets.com/arquivos/ids/6545553/image.jpg?v=638635542271570000InStockMXN99999DIEbook20249789819767694_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_<p>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.</p><p>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.</p>...9789819767694_Springer Nature Singaporelibro_electonico_9789819767694_9789819767694InglésMéxico2024-10-02T00:00:00+00:00Springer Nature Singapore