Frederic ros (52 risultati)
AMC HORS SERIE LOGEMENTS
Hespel, Christophe; Davoine, Gilles; Mialet, Frédéric; Namias, Olivier; Ros, Cyril
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Da: Ammareal, Morangis, , FranciaAmmareal
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Softcover. Condizione: Comme neuf. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, As new. Ammareal gives back up to 15% of this item's net price to charity organizations.
Altre immaginiCatalunya i Espanya: Una relació econòmica i fiscal a revisar (La Mirada) (Catalan Edition)
Francesc Cabana; Antoni Castells; Josep Huguet I Biosca; Francesc Ferrer I Gironès; Guillem López I Casasnovas; Andreu Mas-Colell; Esther Martínez I García; Josep Miró I Ardèvol; Marti Parellada; Ferran Pont I Puntigam; Ferran Requejo; Frederic Ribas; Jacint Ros I Hombravella
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Da: Book-Unin libros, Vic, B, SpagnaBook-Unin libros
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Encuadernación de tapa blanda. Condizione: Muy bueno. 1ª Edición. Primera edició. Com nou per dins, molt bo per fora, nou no està però poc li falta.
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Da: Revaluation Books, Exeter, , Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 52 pages. 8.66x5.91x0.12 inches. In Stock.
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Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. A new density-based sampling for clustering algorithm | Frederic Ros (u. a.) | Taschenbuch | 52 S. | Englisch | 2016 | Scholars' Press | EAN 9783659841354 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Amc, Le Moniteur Architecture, Hors Série. Logement : 30 Projets
Hespel, Christophe; Davoine, Gilles; Mialet, Frédéric; Namias, Olivier; Ros, Cyril
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Da: RECYCLIVRE, Paris, , FranciaRECYCLIVRE
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Condizione: Bon. Merci, votre achat aide à financer des programmes de lutte contre l'illettrisme.
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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EUR 123,33
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Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
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Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
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Paperback. Condizione: new. Paperback. This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major re…cent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by family to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers. This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Da: moluna, Greven, , Germaniamoluna
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Gebunden. Condizione: New.
Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
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Condizione: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
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Condizione: New. pp. XIII, 232 40 illus., 30 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.
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Condizione: New.
Altre immagini- Brossura
Da: preigu, Osnabrück, Germaniapreigu
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Taschenbuch. Condizione: Neu. Sampling Techniques for Supervised or Unsupervised Tasks | Frédéric Ros (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xiii | Englisch | 2020 | Springer | EAN 9783030293512 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[do…t]hartmann[at]springer[dot]com | Anbieter: preigu.
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Taschenbuch. Condizione: Neu. Feature and Dimensionality Reduction for Clustering with Deep Learning | Frederic Ros (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xi | Englisch | 2025 | Springer | EAN 9783031487453 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg…, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Taschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability… and the 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.
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Hardcover. Condizione: Brand New. 248 pages. 9.25x6.10x0.75 inches. In Stock.
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Hardcover. Condizione: Brand New. 279 pages. 9.25x6.10x0.91 inches. In Stock.
Lingua: Inglese
Editore: Springer, Berlin, Springer International Publishing, Springer 2019
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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Buch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing scalability and th…e 'curse of dimensionality', their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the field and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. 'This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge.'M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas'In science the difficulty is not to have ideas, but it is to make them work'From Carlo Rovelli.
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Condizione: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book describes in detail sampling techniques that can be used for unsupervised and supervised cases, with a focus on sampling techniques for machine learning algorithms. It covers theory and models of sampling methods for managing sca…lability and the ¿curse of dimensionality¿, their implementations, evaluations, and applications. A large part of the book is dedicated to database comprising standard feature vectors, and a special section is reserved to the handling of more complex objects and dynamic scenarios. The book is ideal for anyone teaching or learning pattern recognition and interesting teaching or learning pattern recognition and is interested in the big data challenge. It provides an accessible introduction to the ¿eld and discusses the state of the art concerning sampling techniques for supervised and unsupervised task.Provides a comprehensive description of sampling techniques for unsupervised and supervised tasks;Describe implementationand evaluation of algorithms that simultaneously manage scalable problems and curse of dimensionality;Addresses the role of sampling in dynamic scenarios, sampling when dealing with complex objects, and new challenges arising from big data. "This book represents a timely collection of state-of-the art research of sampling techniques, suitable for anyone who wants to become more familiar with these helpful techniques for tackling the big data challenge."M. Emre Celebi, Ph.D., Professor and Chair, Department of Computer Science, University of Central Arkansas"In science the difficulty is not to have ideas, but it is to make them work"From Carlo Rovelli.
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Paperback. Condizione: new. Paperback. This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. The authors first present a synthesis of the major re…cent influencing techniques and "tricks" participating in recent advances in deep clustering, as well as a recall of the main deep learning architectures. Secondly, the book highlights the most popular works by family to provide a more suitable starting point from which to develop a full understanding of the domain. Overall, the book proposes a comprehensive up-to-date review of deep feature selection and deep clustering methods with particular attention to the knowledge discovery question and under a multi-criteria analysis. The book can be very helpful for young researchers, non-experts, and R&D AI engineers. This book presents an overview of recent methods of feature selection and dimensionality reduction that are based on Deep Neural Networks (DNNs) for a clustering perspective, with particular attention to the knowledge discovery question. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Junta d'obra de Santa Maria del Mar, Barcelona 1956
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Da: LIBRERÍA MAESTRO GOZALBO, Carcaixent, V, SpagnaLIBRERÍA MAESTRO GOZALBO
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Condizione: Buen estado. 1ª Edició. Plegado Buen estado.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermaniaBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As clustering algorithms become more and more sophisticated to cope with current needs, large data sets of increasing complexity, sampling is likely to provide an interesting alternative. The main objective of sampling is to select… a part that behaves like the whole. DENDIS is a new algorithm that combines the best of the available techniques in such a way that tractability is actually improved with a user friendly parameter setting. 52 pp. Englisch.
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Da: Majestic Books, Hounslow, , Regno UnitoMajestic Books
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Condizione: New. Print on Demand.
