Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Partitional Clustering Via Nonsmooth Optimization: Clustering Via Optimization

Partitional Clustering Via Nonsmooth Optimization: Clustering Via Optimization

Bagirov, Adil
Karmitsa, Napsu
Taheri, Sona

Hardcover

Series: Unsupervised and Semi-Supervised Learning

Technology & EngineeringGeneral Computers

ISBN10: 3031765117
ISBN13: 9783031765117
Publisher: Springer
Published: Dec 17 2024
Pages: 395
Weight: 1.67
Height: 0.94 Width: 6.14 Depth: 9.21
Language: English

This updated book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering problems; the authors' emphasis on clustering algorithms is based on deterministic methods of optimization. The book also includes results on real-time clustering algorithms based on optimization techniques, addresses implementation issues of these clustering algorithms, and discusses new challenges arising from very large data and data with noise and outliers. The book is ideal for anyone teaching or learning clustering algorithms. It provides an accessible introduction to the field and it is well suited for practitioners already familiar with the basics of optimization.

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