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Advances in Independent Component Analysis and Learning Machines

2015-05-14 Computers
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Release : 2015-05-14
Genre : Computers
Kind : eBook
Book Rating : 076/5 ( reviews)

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Book Synopsis Advances in Independent Component Analysis and Learning Machines by : Ella Bingham

Download or read book Advances in Independent Component Analysis and Learning Machines written by Ella Bingham. This book was released on 2015-05-14. Available in PDF, EPUB and Kindle. Book excerpt: In honour of Professor Erkki Oja, one of the pioneers of Independent Component Analysis (ICA), this book reviews key advances in the theory and application of ICA, as well as its influence on signal processing, pattern recognition, machine learning, and data mining. Examples of topics which have developed from the advances of ICA, which are covered in the book are: A unifying probabilistic model for PCA and ICA Optimization methods for matrix decompositions Insights into the FastICA algorithm Unsupervised deep learning Machine vision and image retrieval A review of developments in the theory and applications of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning A diverse set of application fields, ranging from machine vision to science policy data Contributions from leading researchers in the field

Advances in Independent Component Analysis

2012-12-06 Computers
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Release : 2012-12-06
Genre : Computers
Kind : eBook
Book Rating : 439/5 ( reviews)

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Book Synopsis Advances in Independent Component Analysis by : Mark Girolami

Download or read book Advances in Independent Component Analysis written by Mark Girolami. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: Independent Component Analysis (ICA) is a fast developing area of intense research interest. Following on from Self-Organising Neural Networks: Independent Component Analysis and Blind Signal Separation, this book reviews the significant developments of the past year. It covers topics such as the use of hidden Markov methods, the independence assumption, and topographic ICA, and includes tutorial chapters on Bayesian and variational approaches. It also provides the latest approaches to ICA problems, including an investigation into certain "hard problems" for the very first time. Comprising contributions from the most respected and innovative researchers in the field, this volume will be of interest to students and researchers in computer science and electrical engineering; research and development personnel in disciplines such as statistical modelling and data analysis; bio-informatic workers; and physicists and chemists requiring novel data analysis methods.

Recent Advances in Big Data and Deep Learning

2019-04-02 Computers
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Release : 2019-04-02
Genre : Computers
Kind : eBook
Book Rating : 417/5 ( reviews)

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Book Synopsis Recent Advances in Big Data and Deep Learning by : Luca Oneto

Download or read book Recent Advances in Big Data and Deep Learning written by Luca Oneto. This book was released on 2019-04-02. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the original articles that have been accepted in the 2019 INNS Big Data and Deep Learning (INNS BDDL) international conference, a major event for researchers in the field of artificial neural networks, big data and related topics, organized by the International Neural Network Society and hosted by the University of Genoa. In 2019 INNS BDDL has been held in Sestri Levante (Italy) from April 16 to April 18. More than 80 researchers from 20 countries participated in the INNS BDDL in April 2019. In addition to regular sessions, INNS BDDL welcomed around 40 oral communications, 6 tutorials have been presented together with 4 invited plenary speakers. This book covers a broad range of topics in big data and deep learning, from theoretical aspects to state-of-the-art applications. This book is directed to both Ph.D. students and Researchers in the field in order to provide a general picture of the state-of-the-art on the topics addressed by the conference.

Independent Component Analysis

2004-04-05 Science
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Release : 2004-04-05
Genre : Science
Kind : eBook
Book Rating : 198/5 ( reviews)

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Book Synopsis Independent Component Analysis by : Aapo Hyvärinen

Download or read book Independent Component Analysis written by Aapo Hyvärinen. This book was released on 2004-04-05. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning

2024 Machine learning
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Release : 2024
Genre : Machine learning
Kind : eBook
Book Rating : 958/5 ( reviews)

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Book Synopsis Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning by : ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.)

Download or read book Long-term Structural Health Monitoring by Remote Sensing and Advanced Machine Learning written by ALIREZA. BEHKAMAL ENTEZAMI (BAHAREH. DE MICHELE, CARLO.). This book was released on 2024. Available in PDF, EPUB and Kindle. Book excerpt: This book offers an in-depth investigation into the complexities of long-term structural health monitoring (SHM) in civil structures, specifically focusing on the challenges posed by small data and environmental and operational changes (EOCs). Traditional contact-based sensor networks in SHM produce large amounts of data, complicating big data management. In contrast, synthetic aperture radar (SAR)-aided SHM often faces challenges with small datasets and limited displacement data. Additionally, EOCs can mimic the structural damage, resulting in false errors that can critically affect economic and safety issues. Addressing these challenges, this book introduces seven advanced unsupervised learning methods for SHM, combining AI, data sampling, and statistical analysis. These include techniques for managing datasets and addressing EOCs. Methods range from nearest neighbor searching and Hamiltonian Monte Carlo sampling to innovative offline and online learning frameworks, focusing on data augmentation and normalization. Key approaches involve deep autoencoders for data processing and novel algorithms for damage detection. Validated using simulated data from the I-40 Bridge, USA, and real-world data from the Tadcaster Bridge, UK, these methods show promise in addressing SAR-aided SHM challenges, offering practical tools for real-world applications. The book, thereby, presents a comprehensive suite of innovative strategies to advance the field of SHM.

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