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[null,"1.","Record Nr.",null,"UNINA9910697137503321"]
[null,null,"Autore",null,"Kardous Chucri A"]
[null,null,"Titolo",null,"Reducción de la exposición al plomo y al ruido en campos de tiro cubiertos [[electronic resource] /] / [preparado por Chucri A. Kardous y Susan Afanuh]"]
[null,null,"Pubbl/distr/stampa",null,"[Cincinnati, OH] : , : [Dept. de Salud Y Servicios Humanos, Centros para el Control y la Prevención de Enfermedades, Instituto Nacional para la Seguridad y Salud Ocupacionales], , [2010]"]
[null,null,"Descrizione fisica",null,"1 online resource : illustrations"]
[null,null,"Collana",null,"DHHS (NIOSH) publicación ; ; núm. 2010-113"]
[{"$nulls":4},"Soluciones en la obra"]
[null,null,"Soggetti",null,"Bombing and gunnery ranges"]
[{"$nulls":4},"Deafness, Noise induced - Prevention"]
[{"$nulls":4},"Lead - Toxicology"]
[null,null,"Lingua di pubblicazione",null,"Spagnolo"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Title from caption title screen (NIOSH, viewed Aug. 17, 2010)."]
[{"$nulls":4},"\"Enero de 2010.\""]
[null,null,null,"Nota di bibliografia","Includes bibliographical references."]
[null,"2.","Record Nr.",null,"UNISA996465342403316"]
[null,null,"Autore",null,"Lin Zhouchen"]
[null,null,"Titolo",null,"Accelerated optimization for machine learning : first-order algorithms / / Zhouchen Lin, Huan Li, Cong Fang"]
[null,null,"Pubbl/distr/stampa",null,"Singapore : , : Springer, , [2020]"]
[{"$nulls":4},"©2020"]
[null,null,"ISBN",null,"981-15-2910-8"]
[{"$nulls":4},"9789811529108"]
[null,null,"Descrizione fisica",null,"1 online resource (286 pages)"]
[null,null,"Disciplina",null,"006.31"]
[null,null,"Soggetti",null,"Machine learning - Mathematics"]
[{"$nulls":4},"Mathematical optimization"]
[{"$nulls":4},"Computer mathematics"]
[{"$nulls":4},"Machine Learning"]
[{"$nulls":4},"Optimization"]
[{"$nulls":4},"Math Applications in Computer Science"]
[{"$nulls":4},"Computational Mathematics and Numerical Analysis"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Chapter 1. Introduction -- Chapter 2. Accelerated Algorithms for Unconstrained Convex Optimization -- Chapter 3. Accelerated Algorithms for Constrained Convex Optimization -- Chapter 4. Accelerated Algorithms for Nonconvex Optimization -- Chapter 5. Accelerated Stochastic Algorithms -- Chapter 6. Accelerated Paralleling Algorithms -- Chapter 7. Conclusions."]
[null,null,null,"Sommario/riassunto","This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on optimization to solve problems with its learning models, and first-order optimization algorithms are the mainstream approaches. The acceleration of first-order optimization algorithms is crucial for the efficiency of machine learning. Written by leading experts in the field, this book provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It discusses a variety of methods, including deterministic and stochastic algorithms, where the algorithms can be synchronous or asynchronous, for unconstrained and constrained "]
[{"$nulls":4},"problems, which can be convex or non-convex. Offering a rich blend of ideas, theories and proofs, the book is up-to-date and self-contained. It is an excellent reference resource for users who are seeking faster optimization algorithms, as well as for graduate students and researchers wanting to grasp the frontiers of optimization in machine learning in a short time."]