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Book Advances in Self Organizing Maps  Learning Vector Quantization  Interpretable Machine Learning  and Beyond

Download or read book Advances in Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning and Beyond written by Thomas Villmann and published by Springer Nature. This book was released on with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in Self Organizing Maps  Learning Vector Quantization  Interpretable Machine Learning  and Beyond

Download or read book Advances in Self Organizing Maps Learning Vector Quantization Interpretable Machine Learning and Beyond written by Thomas Villmann and published by Springer. This book was released on 2024-08-30 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps  Learning Vector Quantization  Clustering and Data Visualization

Download or read book Advances in Self Organizing Maps Learning Vector Quantization Clustering and Data Visualization written by Alfredo Vellido and published by Springer. This book was released on 2019-04-27 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps  Learning Vector Quantization  Clustering and Data Visualization

Download or read book Advances in Self Organizing Maps Learning Vector Quantization Clustering and Data Visualization written by Jan Faigl and published by Springer Nature. This book was released on 2022-08-26 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps  Learning Vector Quantization  Clustering and Data Visualization

Download or read book Advances in Self Organizing Maps Learning Vector Quantization Clustering and Data Visualization written by Jan Faigl and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps and Learning Vector Quantization

Download or read book Advances in Self Organizing Maps and Learning Vector Quantization written by Erzsébet Merényi and published by Springer. This book was released on 2016-01-07 with total page 353 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps and Learning Vector Quantization

Download or read book Advances in Self Organizing Maps and Learning Vector Quantization written by Thomas Villmann and published by Springer. This book was released on 2014-06-10 with total page 314 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Advances in Self Organizing Maps

Download or read book Advances in Self Organizing Maps written by Pablo A. Estévez and published by Springer Science & Business Media. This book was released on 2012-12-14 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Self Organizing Maps

    Book Details:
  • Author : Teuvo Kohonen
  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • ISBN : 3642976107
  • Pages : 372 pages

Download or read book Self Organizing Maps written by Teuvo Kohonen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 372 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book we have at hand is the fourth monograph I wrote for Springer Verlag. The previous one named "Self-Organization and Associative Mem ory" (Springer Series in Information Sciences, Volume 8) came out in 1984. Since then the self-organizing neural-network algorithms called SOM and LVQ have become very popular, as can be seen from the many works re viewed in Chap. 9. The new results obtained in the past ten years or so have warranted a new monograph. Over these years I have also answered lots of questions; they have influenced the contents of the present book. I hope it would be of some interest and help to the readers if I now first very briefly describe the various phases that led to my present SOM research, and the reasons underlying each new step. I became interested in neural networks around 1960, but could not in terrupt my graduate studies in physics. After I was appointed Professor of Electronics in 1965, it still took some years to organize teaching at the uni versity. In 1968 - 69 I was on leave at the University of Washington, and D. Gabor had just published his convolution-correlation model of autoasso ciative memory. I noticed immediately that there was something not quite right about it: the capacity was very poor and the inherent noise and crosstalk were intolerable. In 1970 I therefore sugge~ted the auto associative correlation matrix memory model, at the same time as J.A. Anderson and K. Nakano.

Book Advances in Self Organising Maps

Download or read book Advances in Self Organising Maps written by Nigel Allinson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 299 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Advances in Self Organizing Maps

Download or read book Advances in Self Organizing Maps written by Jorma Laaksonen and published by Springer Science & Business Media. This book was released on 2011-06-03 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Workshop on Self-Organizing Maps, WSOM 2011, held in Espoo, Finland, in June 2011. The 36 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on plenaries; financial and societal applications; theory and methodology; applications of data mining and analysis; language processing and document analysis; and visualization and image processing.

Book Advances in Self Organizing Maps

Download or read book Advances in Self Organizing Maps written by J.C. Principe and published by Springer Science & Business Media. This book was released on 2009-05-27 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Workshop on Advances in Self-Organizing Maps, WSOM 2009, held in St. Augustine, Florida, in June 2009. The 41 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers deal with topics in the use of SOM in many areas of social sciences, economics, computational biology, engineering, time series analysis, data visualization and theoretical computer science.

Book Applications of Self Organizing Maps

Download or read book Applications of Self Organizing Maps written by Magnus Johnsson and published by BoD – Books on Demand. This book was released on 2012-11-21 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: The self-organizing map, first described by the Finnish scientist Teuvo Kohonen, can by applied to a wide range of fields. This book is about such applications, i.e. how the original self-organizing map as well as variants and extensions of it can be applied in different fields. In fourteen chapters, a wide range of such applications is discussed. To name a few, these applications include the analysis of financial stability, the fault diagnosis of plants, the creation of well-composed heterogeneous teams and the application of the self-organizing map to the atmospheric sciences.

Book Cognitiva 90

    Book Details:
  • Author :
  • Publisher :
  • Release : 1990
  • ISBN :
  • Pages : 93 pages

Download or read book Cognitiva 90 written by and published by . This book was released on 1990 with total page 93 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book 12th International Workshop on Self Organizing Maps and Learning Vector Quantization  Clustering and Data Visualization  WSOM  2017

Download or read book 12th International Workshop on Self Organizing Maps and Learning Vector Quantization Clustering and Data Visualization WSOM 2017 written by Jean-Charles Lamirel and published by . This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The conference is mainly focused on to the theoretical and methodological aspects of Self Organizing Maps and Learning Vector Quantization More generally, we expect contributions in Data analysis and data visualization, temporal and incremental data mining, various mathematical approaches including information theory and mathematical statistics, software and hardware implementations, architectural solutions including hierarchical and growing networks, ensemble models and special metrics, neuro cognitive studies that compare modeling and empirical results at different levels, models, experimental investigations and applications of autonomous mental development.