Frederic Ros (55 results)
- Softcover
Seller: Hamelyn, Madrid, M, SpainHamelyn
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Condition: Muy bueno. : Este libro analiza las relaciones económicas y fiscales entre Cataluña y España. Profesores y políticos catalanes examinan la historia y la articulación política entre Cataluña y España, la balanza fiscal y de capitales, los flujos fiscales entre Cataluña y Europa, y las consecuencias de la dependencia y…la viabilidad económica de la independencia de Cataluña. El libro intenta responder a la pregunta de qué se hace con el dinero de los catalanes. EAN: 9788482564982 Tipo: Libros Categoría: Negocios y Economía Título: Catalunya i Espanya: Una relació econòmica i fiscal a revisar Autor: 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 Editorial: Proa Idioma: ca Páginas: 342 Formato: tapa dura.
More imagesCatalunya 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
- Softcover
- First Edition
Seller: Book-Unin libros, Vic, B, SpainBook-Unin libros
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Encuadernación de tapa blanda. Condition: Muy bueno. 1ª Edición. Primera edició. Com nou per dins, molt bo per fora, nou no està però poc li falta.
- Softcover
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- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: 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.
Language: English
Published by Springer International Publishing AG, Cham, 2025
- Softcover
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Paperback. Condition: 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 rec…ent 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.
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
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Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
- Softcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
- Hardcover
Seller: Ria Christie Collections, Uxbridge, United KingdomRia Christie Collections
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- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
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- Softcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Paperback. Condition: Brand New. 9.26x6.11 inches. In Stock.
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
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- Hardcover
Seller: moluna, Greven, Germanymoluna
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Gebunden. Condition: New.
Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. 1st ed. 2020 edition NO-PA16APR2015-KAP.
Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. pp. XIII, 232 40 illus., 30 illus. in color. 1st ed. 2020 edition NO-PA16APR2015-KAP.
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New.
- Hardcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condition: New. 1st ed. 2024 edition NO-PA16APR2015-KAP.
More images- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: 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[dot…]hartmann[at]springer[dot]com | Anbieter: preigu.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
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Taschenbuch. Condition: 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.
- Softcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Taschenbuch. Condition: 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.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 248 pages. 9.25x6.10x0.75 inches. In Stock.
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
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Hardcover. Condition: Brand New. 279 pages. 9.25x6.10x0.91 inches. In Stock.
Language: English
Published by Springer, Berlin, Springer International Publishing, Springer, 2019
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Buch. Condition: 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.
- Softcover
Seller: Buchpark, Trebbin, GermanyBuchpark
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Condition: 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 scal…ability 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.
Language: English
Published by Springer International Publishing AG, Cham, 2025
- Softcover
Seller: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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Paperback. Condition: 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 rec…ent 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.
- Softcover
Seller: BUCHSERVICE / ANTIQUARIAT Lars Lutzer, Wahlstedt, GermanyBUCHSERVICE / ANTIQUARIAT Lars Lutzer
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Softcover. Condition: gut. 2020. Sampling Techniques for Supervised or Unsupervised Tasks In deutscher Sprache. pages.
Amc, Le Moniteur Architecture, Hors Série. Logement : 30 Projets
Hespel, Christophe; Davoine, Gilles; Mialet, Frédéric; Namias, Olivier; Ros, Cyril
- Softcover
Seller: RECYCLIVRE, Paris, FranceRECYCLIVRE
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Condition: Bon. Merci, votre achat aide à financer des programmes de lutte contre l'illettrisme.
Published by Junta d'obra de Santa Maria del Mar, Barcelona, 1956
- Art / Print / Poster
Seller: LIBRERÍA MAESTRO GOZALBO, Carcaixent, V, SpainLIBRERÍA MAESTRO GOZALBO
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Add to basketCondition: Buen estado. 1ª Edició. Plegado Buen estado.
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermanyBuchWeltWeit Ludwig Meier e.K.
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Taschenbuch. Condition: 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.
