Che Hangjun (12 results)
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Language: English
Published by The Institution of Engineering and Technology, 2026
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: New
US$ 137.07
US$ 2.64 shippingShips within U.S.A.Quantity: Over 20 available
Condition: 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
Language: English
Published by The Institution of Engineering and Technology, 2026
- Hardcover
Seller: California Books, Miami, FL, U.S.A.California Books
Contact seller4-star sellerCondition: New
US$ 140.00
Free ShippingShips within U.S.A.Quantity: Over 20 available
Condition: New.
Matrix Factorization for Multimedia Clustering : Models, Techniques, Optimization and Applications
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-fai; Pan, Baicheng
Language: English
Published by The Institution of Engineering and Technology, 2026
- Hardcover
Seller: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
Contact seller5-star sellerCondition: Used - As new
US$ 146.64
US$ 2.64 shippingShips within U.S.A.Quantity: Over 20 available
Condition: As New. Unread book in perfect condition.
Matrix Factorization for Multimedia Clustering
Che, Hangjun; Wang, Xin; He, Xing; Leung, Man-Fai; Pan, Baicheng
Language: English
Published by Institution of Engineering and Technology, 2026
- Hardcover
Seller: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
Contact seller5-star sellerCondition: New
US$ 172.64
Free ShippingShips within U.S.A.Quantity: Over 20 available
HRD. Condition: 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
Language: English
Published by Institution of Engineering and Technology, 2026
- Hardcover
Seller: PBShop.store UK, Fairford, GLOS, United KingdomPBShop.store UK
Contact seller5-star sellerCondition: New
US$ 172.69
US$ 6.76 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
HRD. Condition: 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
Language: English
Published by The Institution of Engineering and Technology, 2026
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: Used - As new
US$ 160.50
US$ 20.19 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: 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
Language: English
Published by The Institution of Engineering and Technology, 2026
- Hardcover
Seller: GreatBookPricesUK, Woodford Green, United KingdomGreatBookPricesUK
Contact seller5-star sellerCondition: New
US$ 167.20
US$ 20.19 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Condition: New.
Matrix Factorization for Multimedia Clustering: Models, Techniques, Optimization and Applications
Che, Hangjun/ Wang, Xin/ He, Xing/ Leung, Man-fai/ Pan, Baicheng
- Hardcover
Seller: Revaluation Books, Exeter, United KingdomRevaluation Books
Contact seller5-star sellerCondition: New
US$ 191.71
US$ 16.83 shippingShips from United Kingdom to U.S.A.Quantity: 2 available
Hardcover. Condition: Brand New. 300 pages. 9.21x6.14 inches. In Stock.
- More images
Language: English
Published by Institution Of Engineering & Technology Feb 2026, 2026
- Hardcover
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 199.40
US$ 72.36 shippingShips from Germany to U.S.A.Quantity: 2 available
Buch. Condition: 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.
Language: English
Published by Institution of Engineering and Technology, Stevenage, 2026
- Hardcover
- Print on Demand
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contact seller5-star sellerCondition: New
US$ 139.70
Free ShippingShips within U.S.A.Quantity: 1 available
Hardcover. Condition: 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.
Language: English
Published by Institution of Engineering and Technology, 2026
- Hardcover
- Print on Demand
Seller: THE SAINT BOOKSTORE, Southport, United KingdomTHE SAINT BOOKSTORE
Contact seller5-star sellerCondition: New
US$ 177.87
US$ 21.55 shippingShips from United Kingdom to U.S.A.Quantity: Over 20 available
Hardback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days.
Language: English
Published by Institution of Engineering and Technology, Stevenage, 2025
- Hardcover
- Print on Demand
Seller: CitiRetail, Stevenage, United KingdomCitiRetail
Contact seller5-star sellerCondition: New
US$ 182.30
US$ 49.81 shippingShips from United Kingdom to U.S.A.Quantity: 1 available
Hardcover. Condition: 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.
