Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond - Couverture souple
Synopsis
The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt\-weida), Germany, on July 10–12, 2024.
The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases.
Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Lecture Notes in Networks and Systems)
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond
Edité par
Springer, Berlin, Springer Nature Switzerland, Springer, 2024
ISBN 10 : 3031671589
ISBN 13 : 9783031671586
Neuf
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt-weida), Germany, on July 10-12, 2024.The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases. Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization. 228 pp. Englisch. N° de réf. du vendeur 9783031671586
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Lecture Notes in Networks and Systems)
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond | Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10-12, 2024
Edité par
Springer Nature Switzerland, 2024
ISBN 10 : 3031671589
ISBN 13 : 9783031671586
Neuf
Taschenbuch
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Taschenbuch. Etat : Neu. Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond | Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10-12, 2024 | Thomas Villmann (u. a.) | Taschenbuch | xiii | Englisch | 2024 | Springer Nature Switzerland | EAN 9783031671586 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 129529578
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond
ISBN 10 : 3031671589
ISBN 13 : 9783031671586
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
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Taschenbuch. Etat : Neu. Neuware -The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt-weida), Germany, on July 10¿12, 2024.The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases.Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 244 pp. Englisch. N° de réf. du vendeur 9783031671586
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Lecture Notes in Networks and Systems)
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond : Proceedings of the 15th International Workshop, WSOM+ 2024, Mittweida, Germany, July 10¿12, 2024
Edité par
Springer Nature Switzerland, 2024
ISBN 10 : 3031671589
ISBN 13 : 9783031671586
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt-weida), Germany, on July 10-12, 2024.The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases. Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization. N° de réf. du vendeur 9783031671586
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Paperback)
Edité par
Springer International Publishing AG, Cham, 2024
ISBN 10 : 3031671589
ISBN 13 : 9783031671586
Neuf
Paperback
Vendeur : CitiRetail, Stevenage, Royaume-Uni
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Paperback. Etat : new. Paperback. The book presents the peer-reviewed contributions of the 15th International Workshop on Self-Organizing Maps, Learning Vector Quantization and Beyond (WSOM$+$ 2024), held at the University of Applied Sciences Mittweida (UAS Mitt\-weida), Germany, on July 1012, 2024.The book highlights new developments in the field of interpretable and explainable machine learning for classification tasks, data compression and visualization. Thereby, the main focus is on prototype-based methods with inherent interpretability, computational sparseness and robustness making them as favorite methods for advanced machine learning tasks in a wide variety of applications ranging from biomedicine, space science, engineering to economics and social sciences, for example. The flexibility and simplicity of those approaches also allow the integration of modern aspects such as deep architectures, probabilistic methods and reasoning as well as relevance learning. The book reflects both new theoretical aspects in this research area and interesting application cases. Thus, this book is recommended for researchers and practitioners in data analytics and machine learning, especially those who are interested in the latest developments in interpretable and robust unsupervised learning, data visualization, classification and self-organization. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9783031671586
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Lecture Notes in Networks and Systems)
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
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Advances in Self-Organizing Maps, Learning Vector Quantization, Interpretable Machine Learning, and Beyond (Lecture Notes in Networks and Systems)
impression à la demandeVendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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