Hangjun che (12 resultados)
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2026
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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 123,12
Envío por EUR 2,30Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications (Computing and Networks)
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2026
- Tapa dura
Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books
Contactar con el vendedorVendedor de 4 estrellasCondición: Nuevo
EUR 125,75
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2026
- Tapa dura
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 131,72
Envío por EUR 2,30Se envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
Matrix Factorization for Multimedia Clustering
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
- Tapa dura
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de AmericaPBShop.store US
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 155,07
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Matrix Factorization for Multimedia Clustering
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
- Tapa dura
Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 149,55
Envío por EUR 5,85Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
HRD. Condición: New. New Book. Shipped from UK. Established seller since 2000.
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2026
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Usado - Como Nuevo
EUR 138,98
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: As New. Unread book in perfect condition.
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Idioma: Inglés
Editorial: The Institution of Engineering and Technology, 2026
- Tapa dura
Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 144,79
Envío por EUR 17,49Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Condición: New.
Matrix Factorization for Multimedia Clustering: Models, Techniques, Optimization and Applications
Che, Hangjun/ Wang, Xin/ He, Xing/ Leung, Man-fai/ Pan, Baicheng
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Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books
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EUR 166,02
Envío por EUR 14,57Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Hardcover. Condición: Brand New. 300 pages. 9.21x6.14 inches. In Stock.
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Idioma: Inglés
Editorial: Institution Of Engineering & Technology Feb 2026, 2026
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 168,00
Envío por EUR 62,79Se envía de Alemania a Estados Unidos de AmericaCantidad disponible: 2 disponibles
Buch. Condición: Neu. Neuware - Clustering is a fundamental problem in multimedia information processing. This co-authored book explores clustering principles through advanced data analysis techniques, such as matrix and tensor factorization, which are highly relevant for multimedia information processing. Multimedia data may ex…hibit various forms of noise represented from multiple perspectives, making traditional clustering approaches less effective. The authors consider complex conditions such as noise sensitivity and discuss methods to address these challenges in the context of multimedia data. They also examine popular regularization techniques, providing theoretical analyses that demonstrate the relationship between regularization and clustering performance. Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications will serve as a solid advanced reference for researchers, scientists, engineers and advanced students who wish to implement practical tasks through clustering formulations. Additionally, the authors provide a detailed description of convergence theory to enable readers to conduct the corresponding algorithm analyses. They investigate novel regularization techniques, such as self-paced learning, optimal graph learning, and diversity regularization, to uncover the geometric structure of data. These techniques are beneficial for enhancing clustering performance. Furthermore, they demonstrate the efficiency of these regularization techniques through theoretical analyses, practical experiments and applications in real-world datasets.
Idioma: Inglés
Editorial: Institution of Engineering and Technology, Stevenage, 2026
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- Impresión bajo demanda
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 125,48
Gastos de envío gratisSe envía dentro de Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Clustering is a fundamental problem in multimedia information processing. This co-authored book explores clustering principles through advanced data analysis techniques, such as matrix and tensor factorization, which are highly relevant for multimedia information processing. Multimedia data…may exhibit various forms of noise represented from multiple perspectives, making traditional clustering approaches less effective. The authors consider complex conditions such as noise sensitivity and discuss methods to address these challenges in the context of multimedia data. They also examine popular regularization techniques, providing theoretical analyses that demonstrate the relationship between regularization and clustering performance.Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications will serve as a solid advanced reference for researchers, scientists, engineers and advanced students who wish to implement practical tasks through clustering formulations. Additionally, the authors provide a detailed description of convergence theory to enable readers to conduct the corresponding algorithm analyses. They investigate novel regularization techniques, such as self-paced learning, optimal graph learning, and diversity regularization, to uncover the geometric structure of data. These techniques are beneficial for enhancing clustering performance. Furthermore, they demonstrate the efficiency of these regularization techniques through theoretical analyses, practical experiments and applications in real-world datasets. This book explores clustering principles through advanced data analysis techniques, such as matrix and tensor factorization in multimedia information processing. The authors present methods to address these challenges, examine popular regularization techniques, and explore the relationship between regularization and clustering performance. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 154,03
Envío por EUR 18,66Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: Más de 20 disponibles
Hardback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Idioma: Inglés
Editorial: Institution of Engineering and Technology, Stevenage, 2025
- Tapa dura
- Impresión bajo demanda
Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail
Contactar con el vendedorVendedor de 5 estrellasCondición: Nuevo
EUR 157,87
Envío por EUR 43,13Se envía de Reino Unido a Estados Unidos de AmericaCantidad disponible: 1 disponibles
Hardcover. Condición: new. Hardcover. Clustering is a fundamental problem in multimedia information processing. This co-authored book explores clustering principles through advanced data analysis techniques, such as matrix and tensor factorization, which are highly relevant for multimedia information processing. Multimedia data…may exhibit various forms of noise represented from multiple perspectives, making traditional clustering approaches less effective. The authors consider complex conditions such as noise sensitivity and discuss methods to address these challenges in the context of multimedia data. They also examine popular regularization techniques, providing theoretical analyses that demonstrate the relationship between regularization and clustering performance.Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications will serve as a solid advanced reference for researchers, scientists, engineers and advanced students who wish to implement practical tasks through clustering formulations. Additionally, the authors provide a detailed description of convergence theory to enable readers to conduct the corresponding algorithm analyses. They investigate novel regularization techniques, such as self-paced learning, optimal graph learning, and diversity regularization, to uncover the geometric structure of data. These techniques are beneficial for enhancing clustering performance. Furthermore, they demonstrate the efficiency of these regularization techniques through theoretical analyses, practical experiments and applications in real-world datasets. This book explores clustering principles through advanced data analysis techniques, such as matrix and tensor factorization in multimedia information processing. The authors present methods to address these challenges, examine popular regularization techniques, and explore the relationship between regularization and clustering performance. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
