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Advances In Self Organizing Maps Learning Vector Quantization Clustering And Data Visualization

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

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Author: Alfredo Vellido
Publisher: Springer
ISBN: 3030196429
Size: 24.92 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 342
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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 And Learning Vector Quantization

Advances in Self Organizing Maps and Learning Vector Quantization PDF

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Author: Thomas Villmann
Publisher: Springer
ISBN: 3319076957
Size: 41.38 MB
Format: PDF, Mobi
Category : Technology & Engineering
Languages : en
Pages : 314
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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 And Learning Vector Quantization

Advances in Self Organizing Maps and Learning Vector Quantization PDF

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Author: Erzsébet Merényi
Publisher: Springer
ISBN: 3319285181
Size: 62.31 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 370
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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

Advances in Self Organizing Maps PDF

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Author: Pablo A. Estévez
Publisher: Springer Science & Business Media
ISBN: 3642352308
Size: 26.30 MB
Format: PDF
Category : Computers
Languages : en
Pages : 364
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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.

Modelling And Simulation For Autonomous Systems

Modelling and Simulation for Autonomous Systems PDF

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Author: Jan Mazal
Publisher: Springer Nature
ISBN: 3030438902
Size: 27.92 MB
Format: PDF, ePub
Category : Computers
Languages : en
Pages : 440
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This book constitutes the thoroughly refereed post-workshop proceedings of the 6th International Workshop on Modelling and Simulation for Autonomous Systems, MESAS 2019, held in Palermo, Italy, in October 2019. The 22 full papers and 13 short papers included in the volume were carefully reviewed and selected from 53 submissions. They are organized in the following topical sections: M&S of intelligent systems - AI, R&D and application; future challenges of advanced M&S technology; AxS in context of future warfare and security environment (concepts, applications, training, interoperability, etc.).

Advances In Self Organizing Maps

Advances in Self Organizing Maps PDF

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Author: Jorma Laaksonen
Publisher: Springer Science & Business Media
ISBN: 3642215653
Size: 75.63 MB
Format: PDF, Kindle
Category : Computers
Languages : en
Pages : 368
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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.

Advances In Computational Intelligence

Advances in Computational Intelligence PDF

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Author: Ignacio Rojas
Publisher: Springer
ISBN: 3030205215
Size: 15.12 MB
Format: PDF, ePub, Mobi
Category : Computers
Languages : en
Pages : 940
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This two-volume set LNCS 10305 and LNCS 10306 constitutes the refereed proceedings of the 15th International Work-Conference on Artificial Neural Networks, IWANN 2019, held at Gran Canaria, Spain, in June 2019. The 150 revised full papers presented in this two-volume set were carefully reviewed and selected from 210 submissions. The papers are organized in topical sections on machine learning in weather observation and forecasting; computational intelligence methods for time series; human activity recognition; new and future tendencies in brain-computer interface systems; random-weights neural networks; pattern recognition; deep learning and natural language processing; software testing and intelligent systems; data-driven intelligent transportation systems; deep learning models in healthcare and biomedicine; deep learning beyond convolution; artificial neural network for biomedical image processing; machine learning in vision and robotics; system identification, process control, and manufacturing; image and signal processing; soft computing; mathematics for neural networks; internet modeling, communication and networking; expert systems; evolutionary and genetic algorithms; advances in computational intelligence; computational biology and bioinformatics.

Advances In Self Organizing Maps

Advances in Self Organizing Maps PDF

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Author: J.C. Principe
Publisher: Springer Science & Business Media
ISBN: 3642023967
Size: 67.78 MB
Format: PDF, ePub, Docs
Category : Computers
Languages : en
Pages : 374
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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.

Kohonen Maps

Kohonen Maps PDF

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Author: E. Oja
Publisher: Elsevier
ISBN: 9780080535296
Size: 70.60 MB
Format: PDF, Docs
Category : Computers
Languages : en
Pages : 400
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The Self-Organizing Map, or Kohonen Map, is one of the most widely used neural network algorithms, with thousands of applications covered in the literature. It was one of the strong underlying factors in the popularity of neural networks starting in the early 80's. Currently this method has been included in a large number of commercial and public domain software packages. In this book, top experts on the SOM method take a look at the state of the art and the future of this computing paradigm. The 30 chapters of this book cover the current status of SOM theory, such as connections of SOM to clustering, classification, probabilistic models, and energy functions. Many applications of the SOM are given, with data mining and exploratory data analysis the central topic, applied to large databases of financial data, medical data, free-form text documents, digital images, speech, and process measurements. Biological models related to the SOM are also discussed.

Advances In Intelligent Data Analysis

Advances in Intelligent Data Analysis PDF

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Author:
Publisher:
ISBN:
Size: 37.44 MB
Format: PDF, Mobi
Category : Expert systems (Computer science)
Languages : en
Pages :
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