Advances In Self Organizing Maps And Learning Vector Quantization
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Advances In Self Organizing Maps And Learning Vector Quantization
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Author : Thomas Villmann
language : en
Publisher: Springer
Release Date : 2014-06-10
Advances In Self Organizing Maps And Learning Vector Quantization written by Thomas Villmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-10 with Technology & Engineering categories.
The book collects the scientific contributions presented at the 10th Workshop on Self-Organizing Maps (WSOM 2014) held at the University of Applied Sciences Mittweida, Mittweida (Germany, Saxony), on July 2–4, 2014. Starting with the first WSOM-workshop 1997 in Helsinki this workshop focuses on newest results in the field of supervised and unsupervised vector quantization like self-organizing maps for data mining and data classification. This 10th WSOM brought together more than 50 researchers, experts and practitioners in the beautiful small town Mittweida in Saxony (Germany) nearby the mountains Erzgebirge to discuss new developments in the field of unsupervised self-organizing vector quantization systems and learning vector quantization approaches for classification. The book contains the accepted papers of the workshop after a careful review process as well as summaries of the invited talks. Among these book chapters there are excellent examples of the use of self-organizing maps in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis and time series analysis. Other chapters present the latest theoretical work on self-organizing maps as well as learning vector quantization methods, such as relating those methods to classical statistical decision methods. All the contribution demonstrate that vector quantization methods cover a large range of application areas including data visualization of high-dimensional complex data, advanced decision making and classification or data clustering and data compression.
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization
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Author : Alfredo Vellido
language : en
Publisher: Springer
Release Date : 2019-04-27
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization written by Alfredo Vellido and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-27 with Computers categories.
This book gathers papers presented at the 13th International Workshop on Self-Organizing Maps, Learning Vector Quantization, Clustering and Data Visualization (WSOM+), which was held in Barcelona, Spain, from the 26th to the 28th of June 2019. Since being founded in 1997, the conference has showcased the state of the art in unsupervised machine learning methods related to the successful and widely used self-organizing map (SOM) method, and extending its scope to clustering and data visualization. In this installment of the AISC series, the reader will find theoretical research on SOM, LVQ and related methods, as well as numerous applications to problems in fields ranging from business and engineering to the life sciences. Given the scope of its coverage, the book will be of interest to machine learning researchers and practitioners in general and, more specifically, to those looking for the latest developments in unsupervised learning and data visualization.
Advances In Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning And Beyond
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Author : Thomas Villmann
language : en
Publisher: Springer Nature
Release Date : 2024-08-01
Advances In Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning And Beyond written by Thomas Villmann and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-01 with Computers categories.
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.
Advances In Self Organizing Maps And Learning Vector Quantization
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Author : Erzsébet Merényi
language : en
Publisher: Springer
Release Date : 2016-01-07
Advances In Self Organizing Maps And Learning Vector Quantization written by Erzsébet Merényi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-07 with Technology & Engineering categories.
This book contains the articles from the international conference 11th Workshop on Self-Organizing Maps 2016 (WSOM 2016), held at Rice University in Houston, Texas, 6-8 January 2016. WSOM is a biennial international conference series starting with WSOM'97 in Helsinki, Finland, under the guidance and direction of Professor Tuevo Kohonen (Emeritus Professor, Academy of Finland). WSOM brings together the state-of-the-art theory and applications in Competitive Learning Neural Networks: SOMs, LVQs and related paradigms of unsupervised and supervised vector quantization.The current proceedings present the expert body of knowledge of 93 authors from 15 countries in 31 peer reviewed contributions. It includes papers and abstracts from the WSOM 2016 invited speakers representing leading researchers in the theory and real-world applications of Self-Organizing Maps and Learning Vector Quantization: Professor Marie Cottrell (Universite Paris 1 Pantheon Sorbonne, France), Professor Pablo Estevez (University of Chile and Millennium Instituteof Astrophysics, Chile), and Professor Risto Miikkulainen (University of Texas at Austin, USA). The book comprises a diverse set of theoretical works on Self-Organizing Maps, Neural Gas, Learning Vector Quantization and related topics, and an excellent variety of applications to data visualization, clustering, classification, language processing, robotic control, planning, and to the analysis of astronomical data, brain images, clinical data, time series, and agricultural data.
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization
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Author : Jan Faigl
language : en
Publisher: Springer Nature
Release Date : 2022-08-26
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization written by Jan Faigl and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-26 with Technology & Engineering categories.
In this collection, the reader can find recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional fields of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, specifically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization
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Author : Jan Faigl
language : en
Publisher:
Release Date : 2022
Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization written by Jan Faigl and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
In this collection, the reader can find recent advancements in self-organizing maps (SOMs) and learning vector quantization (LVQ), including progressive ideas on exploiting features of parallel computing. The collection is balanced in presenting novel theoretical contributions with applied results in traditional fields of SOMs, such as visualization problems and data analysis. Besides, the collection further includes less traditional deployments in trajectory clustering and recent results on exploiting quantum computation. The presented book is worth interest to data analysis and machine learning researchers and practitioners, specifically those interested in being updated with current developments in unsupervised learning, data visualization, and self-organization.
Advances In Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning And Beyond
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Author : Thomas Villmann
language : en
Publisher:
Release Date : 2024
Advances In Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning And Beyond written by Thomas Villmann and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with categories.
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.
Advances In Self Organizing Maps
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Author : Pablo A. Estévez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-14
Advances In Self Organizing Maps written by Pablo A. Estévez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-14 with Technology & Engineering categories.
Self-organizing maps (SOMs) were developed by Teuvo Kohonen in the early eighties. Since then more than 10,000 works have been based on SOMs. SOMs are unsupervised neural networks useful for clustering and visualization purposes. Many SOM applications have been developed in engineering and science, and other fields. This book contains refereed papers presented at the 9th Workshop on Self-Organizing Maps (WSOM 2012) held at the Universidad de Chile, Santiago, Chile, on December 12-14, 2012. The workshop brought together researchers and practitioners in the field of self-organizing systems. Among the book chapters there are excellent examples of the use of SOMs in agriculture, computer science, data visualization, health systems, economics, engineering, social sciences, text and image analysis, and time series analysis. Other chapters present the latest theoretical work on SOMs as well as Learning Vector Quantization (LVQ) methods.
Advances In Self Organising Maps
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Author : Nigel Allinson
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Advances In Self Organising Maps written by Nigel Allinson and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This is the third Workshop on Self-Organising Maps (WSOM) and its related techniques. The previous two were held in Helsinki (1997 and 1999) and confIrmed the vitality of the SOM as one of the most popular and powerful concepts for unsupervised pattern recognition and data visualisation. These meetings not only acted as a showcase for the latest advances in SOM theory and for illustrating its vast range of applicability, but also as venues where much informal and fruitful interaction could take place. It is interesting to observe the development of the original SOM, and this remarkable progress confrrms the originality and insight of Teuvo Kohonen's pioneering work. With the range and quality of the papers in this volume, the stage is set for another very successful meeting. This volume is a permanent record of all the contributions presented during WSOM'OI held at the University of Lincolnshire and Humberside, 13 - 15 June, 2001. The University is the newest of England's universities but it is situated in the heart of one of our oldest cities - founded by the Romans and overlooked by the towering mass of its medieval cathedral. Primarily Lincoln has always been a centre for the rich agricultural heartland of England; however, it was the birthplace, 186 years ago, of George Boole. So WSOM'OI is continuing Lincoln's long and honourable tradition of advancing scientific understanding.
Artificial Neural Networks
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Author :
language : en
Publisher:
Release Date : 2002
Artificial Neural Networks written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Neural networks (Computer science) categories.