Fuwei (53 resultados)
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Librería: Anybook.com, Lincoln, Reino UnidoAnybook.com
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Pobre
EUR 11,36
Envío por EUR 15,78Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Poor. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In poor condition, suitable as a reading copy. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,550grams, ISBN:9787119004310.
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Librería: Cotswold Internet Books, Cheltenham, Reino UnidoCotswold Internet Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado
EUR 11,23
Envío por EUR 16,24Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Used - Very Good. VG paperback. Beijing. With maps & colour & B&W illustrations. Slight rippling to front & back cover (binding fault), otherwise a clean, tidy copy Used - Very Good. VG paperback.
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Librería: liu xing, Nanjing, JS, Chinaliu xing
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 55,63
Envío por EUR 15,82Se envía de China a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Soft cover. Condición: New. Language:English.Author:She Fuwei.Binding:Soft Cover.Publisher:Foreign Languages Press.
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Librería: ReadCNBook, Nanjing, JS, ChinaReadCNBook
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Aceptable
EUR 79,32
Envío por EUR 15,82Se envía de China a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: Good. HardCover. Number of Pages: 432 Pages. Language: English. The main focus of the book includes threes aspects: first. an introduction of the historic bridges and passages of the East-West cultural exchange; second. an explanation of the scope and scale of such exchanges; and. third. an analysis of the…interaction of Chinese and foreign cultures and a look at the future of Chinese culture.
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Librería: BennettBooksLtd, Los Angeles, CA, Estados Unidos de AmericaBennettBooksLtd
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 89,74
Envío por EUR 6,11Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Paperback. Condición: New. In shrink wrap. Looks like an interesting title.
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Librería: liu xing, Nanjing, JS, Chinaliu xing
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 83,85
Envío por EUR 15,82Se envía de China a Estados Unidos de AmericaCantidad disponible: 10 disponibles
Hardcover. Condición: New. Language:English.Author:Shen Fuwei.Binding:HardCover.Publisher:Foreign Languages Press.
Idioma: Inglés
Editorial: Beijing, Foreign Languagees Press 1996
- Primera edición
Librería: ACADEMIA Antiquariat an der Universität, Freiburg, AlemaniaACADEMIA Antiquariat an der Universität
Contactar con el vendedorVendedor de 5 estrellasMiembro de asociación: BOEV
Condición: Usado - Excelente
EUR 30,00
Envío por EUR 34,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
14 x 20 cm. Condición: Sehr gut. 1. Aufl. 416 Seiten / pages heller broschierter Band im Oktavformat; sehr gutes Exemplar mit einigen Abbildungen auf Bildertafeln und 2 Karten / well-kept copy with some plates) Sprache: Englisch Gewicht in Gramm: 1.
Editorial: Foreign Languages Press, Beijing 1997
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Librería: J. Wyatt Books, Ottawa, ON, CanadaJ. Wyatt Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Muy bueno
EUR 41,63
Envío por EUR 20,21Se envía de Canada a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Soft cover. Condición: Near Fine. 416 pages in excellent condition. Includes colour, b/w illustrations and two fold-out maps. White card covers with black titles. Very light wear on corners, small tear at head of spine. NEAR FINE. Book.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 138,75
Envío por EUR 2,32Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
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- Primera edición
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 141,15
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal proce…ssing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 140,21
Envío por EUR 13,90Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. In.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 143,36
Envío por EUR 11,60Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: Brand New. 113 pages. 9.25x6.10x0.59 inches. In Stock.
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Librería: Ria Christie Collections, Uxbridge, Reino UnidoRia Christie Collections
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 140,21
Envío por EUR 13,90Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New. In.
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 155,32
Envío por EUR 2,32Se envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: As New. Unread book in perfect condition.
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 140,20
Envío por EUR 17,40Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: New.
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 155,54
Envío por EUR 17,40Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: As New. Unread book in perfect condition.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer 2023
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Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 127,40
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Idioma: Inglés
Editorial: Springer, Berlin|Springer International Publishing|Springer 2022
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Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 127,40
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
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Librería: Buchpark, Trebbin, AlemaniaBuchpark
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Excelente
EUR 80,99
Envío por EUR 105,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the autho…rs reveal the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 198,63
Envío por EUR 3,51Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 199,58
Envío por EUR 3,51Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. pp. 116.
Idioma: Inglés
Editorial: Springer, Berlin|Springer Nature Singapore|Shanghai People's Publishing House|Chinese Fund for the Humanities and Social Sciences|Palgrave Macmillan 2024
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Librería: moluna, Greven, Alemaniamoluna
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 146,12
Envío por EUR 48,99Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Gebunden. Condición: New.
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Librería: preigu, Osnabrück, Alemaniapreigu
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 131,05
Envío por EUR 70,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 5 disponibles
Taschenbuch. Condición: Neu. Machine Learning Algorithms | Adversarial Robustness in Signal Processing | Fuwei Li (u. a.) | Taschenbuch | Wireless Networks | ix | Englisch | 2023 | Springer | EAN 9783031163777 | 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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Librería: Buchpark, Trebbin, AlemaniaBuchpark
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado
EUR 102,76
Envío por EUR 105,00Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, t…he authors reveal the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 149,79
Envío por EUR 61,74Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book demonstratesthe optimal adversarial attacks against several important signal processing algorithms.Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal… the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.
Idioma: Inglés
Editorial: Springer International Publishing, Springer International Publishing 2023
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 149,79
Envío por EUR 60,95Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book demonstratesthe optimal adversarial attacks against several important signal processing algorithms.Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors… reveal the robustness of the signal processing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 221,04
Envío por EUR 11,60Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Paperback. Condición: Brand New. 113 pages. 9.25x6.10x0.27 inches. In Stock.
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Librería: Books Puddle, New York, NY, Estados Unidos de AmericaBooks Puddle
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 229,83
Envío por EUR 3,51Se envía dentro de Estados Unidos de AmericaCantidad disponible: 4 disponibles
Condición: New. 2024th edition NO-PA16APR2015-KAP.
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 223,02
Envío por EUR 11,60Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: Brand New. 113 pages. 9.25x6.10x0.59 inches. In Stock.
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- Primera edición
Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 203,68
Envío por EUR 32,51Se envía de Australia a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. This book demonstrates the optimal adversarial attacks against several important signal processing algorithms. Through presenting the optimal attacks in wireless sensor networks, array signal processing, principal component analysis, etc, the authors reveal the robustness of the signal proce…ssing algorithms against adversarial attacks. Since data quality is crucial in signal processing, the adversary that can poison the data will be a significant threat to signal processing. Therefore, it is necessary and urgent to investigate the behavior of machine learning algorithms in signal processing under adversarial attacks. The authors in this book mainly examine the adversarial robustness of three commonly used machine learning algorithms in signal processing respectively: linear regression, LASSO-based feature selection, and principal component analysis (PCA). As to linear regression, the authors derive the optimal poisoning data sample and the optimal feature modifications, and also demonstrate the effectiveness of the attack against a wireless distributed learning system. The authors further extend the linear regression to LASSO-based feature selection and study the best strategy to mislead the learning system to select the wrong features. The authors find the optimal attack strategy by solving a bi-level optimization problem and also illustrate how this attack influences array signal processing and weather data analysis. In the end, the authors consider the adversarial robustness of the subspace learning problem. The authors examine the optimal modification strategy under the energy constraints to delude the PCA-based subspace learning algorithm. This book targets researchers working in machine learning, electronic information, and information theory as well as advanced-level students studying these subjects. R&D engineers who are working in machine learning, adversarial machine learning, robust machine learning, and technical consultants working on the security and robustness of machine learning are likely to purchase this book as a reference guide. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
