LEADER 03746nam 22007095 450 001 9910983338603321 005 20251113185942.0 010 $a9783031765124 010 $a3031765125 024 7 $a10.1007/978-3-031-76512-4 035 $a(CKB)37037387500041 035 $a(MiAaPQ)EBC31849560 035 $a(Au-PeEL)EBL31849560 035 $a(DE-He213)978-3-031-76512-4 035 $a(EXLCZ)9937037387500041 100 $a20241216d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPartitional Clustering via Nonsmooth Optimization $eClustering via Optimization /$fby Adil Bagirov, Napsu Karmitsa, Sona Taheri 205 $a2nd ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (402 pages) 225 1 $aUnsupervised and Semi-Supervised Learning,$x2522-8498 311 08$a9783031765117 311 08$a3031765117 327 $aIntroduction -- Introduction to Clustering -- Clustering Algorithms -- Nonsmooth Optimization Models in Cluster Analysis -- Nonsmooth Optimization -- Optimization based Clustering Algorithms -- Implementation and Numerical Results -- Conclusion. 330 $aThis updated book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering problems; the authors' emphasis on clustering algorithms is based on deterministic methods of optimization. The book also includes results on real-time clustering algorithms based on optimization techniques, addresses implementation issues of these clustering algorithms, and discusses new challenges arising from very large data and data with noise and outliers. The book is ideal for anyone teaching or learning clustering algorithms. It provides an accessible introduction to the ?eld and it is well suited for practitioners already familiar with the basics of optimization. Designed for a typical undergraduate, graduate, or dual-listed course with a semester-based calendar; Puts theory in context, so readers gain knowledge about the most essential concepts and algorithms; Covers essential terms, algorithms, and useful tools for learning and performing contemporary AI. 410 0$aUnsupervised and Semi-Supervised Learning,$x2522-8498 606 $aTelecommunication 606 $aPattern recognition systems 606 $aSignal processing 606 $aArtificial intelligence 606 $aData mining 606 $aCommunications Engineering, Networks 606 $aAutomated Pattern Recognition 606 $aSignal, Speech and Image Processing 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 615 0$aTelecommunication. 615 0$aPattern recognition systems. 615 0$aSignal processing. 615 0$aArtificial intelligence. 615 0$aData mining. 615 14$aCommunications Engineering, Networks. 615 24$aAutomated Pattern Recognition. 615 24$aSignal, Speech and Image Processing. 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 676 $a621.382 700 $aBag??rov$b Adil$01864776 701 $aKarmitsa$b Napsu$01296135 701 $aTaheri$b Sona$01785147 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910983338603321 996 $aPartitional Clustering via Nonsmooth Optimization$94526990 997 $aUNINA