Hangjun (12 Ergebnisse)
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Sprache: Englisch
Verlag: The Institution of Engineering and Technology 2026
- Hardcover
Anbieter: GreatBookPrices, Columbia, MD, USAGreatBookPrices
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EUR 124,48
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Matrix Factorization for Multimedia Clustering: Models, techniques, optimization and applications (Computing and Networks)
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
Sprache: Englisch
Verlag: The Institution of Engineering and Technology 2026
- Hardcover
Anbieter: California Books, Miami, FL, USACalifornia Books
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EUR 126,92
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Zustand: New.
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Sprache: Englisch
Verlag: The Institution of Engineering and Technology 2026
- Hardcover
Anbieter: GreatBookPrices, Columbia, MD, USAGreatBookPrices
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EUR 132,69
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Zustand: 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
Sprache: Englisch
Verlag: The Institution of Engineering and Technology 2026
- Hardcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
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EUR 139,49
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Zustand: 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
Sprache: Englisch
Verlag: The Institution of Engineering and Technology 2026
- Hardcover
Anbieter: GreatBookPricesUK, Woodford Green, Vereinigtes KönigreichGreatBookPricesUK
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EUR 145,98
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Zustand: New.
Matrix Factorization for Multimedia Clustering: Models, Techniques, Optimization and Applications
Che, Hangjun/ Wang, Xin/ He, Xing/ Leung, Man-fai/ Pan, Baicheng
- Hardcover
Anbieter: Revaluation Books, Exeter, Vereinigtes KönigreichRevaluation Books
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EUR 166,36
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Hardcover. Zustand: Brand New. 300 pages. 9.21x6.14 inches. In Stock.
Sprache: Englisch
Verlag: Institution Of Engineering & Technology Feb 2026 2026
- Hardcover
Anbieter: AHA-BUCH GmbH, Einbeck, DeutschlandAHA-BUCH GmbH
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EUR 197,99
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Buch. Zustand: 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 exhi…bit 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.
Sprache: Englisch
Verlag: Institution of Engineering and Technology, Stevenage 2026
- Hardcover
- Print-on-Demand
Anbieter: Grand Eagle Retail, Bensenville, IL, USAGrand Eagle Retail
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EUR 126,87
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Hardcover. Zustand: 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 ma…y 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.
Matrix Factorization for Multimedia Clustering
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
- Hardcover
- Print-on-Demand
Anbieter: PBShop.store UK, Fairford, GLOS, Vereinigtes KönigreichPBShop.store UK
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EUR 148,91
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HRD. Zustand: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
Matrix Factorization for Multimedia Clustering
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
- Hardcover
- Print-on-Demand
Anbieter: PBShop.store US, Wood Dale, IL, USAPBShop.store US
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EUR 156,54
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HRD. Zustand: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
- Hardcover
- Print-on-Demand
Anbieter: THE SAINT BOOKSTORE, Southport, Vereinigtes KönigreichTHE SAINT BOOKSTORE
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EUR 154,58
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Hardback. Zustand: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Sprache: Englisch
Verlag: Institution of Engineering and Technology, Stevenage 2025
- Hardcover
- Print-on-Demand
Anbieter: CitiRetail, Stevenage, Vereinigtes KönigreichCitiRetail
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EUR 157,19
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Hardcover. Zustand: 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 ma…y 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.
