Advances in Independent Component Analysis and Learning Machines

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.

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  • Author : Ella Bingham
  • Publisher : Academic Press
  • Pages : 328 pages
  • ISBN : 0128028076
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKAdvances in Independent Component Analysis and Learning Machines

Advances in Independent Component Analysis and Learning Machines

Advances in Independent Component Analysis and Learning Machines
  • Author : Ella Bingham,Samuel Kaski,Jorma Laaksonen,Jouko Lampinen
  • Publisher : Academic Press
  • Release : 14 May 2015
GET THIS BOOKAdvances in Independent Component Analysis and Learning Machines

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

Advances in Independent Component Analysis

Advances in Independent Component Analysis
  • Author : Mark Girolami
  • Publisher : Springer Science & Business Media
  • Release : 17 July 2000
GET THIS BOOKAdvances in Independent Component Analysis

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

Recent Advances in Big Data and Deep Learning

Recent Advances in Big Data and Deep Learning
  • Author : Luca Oneto,Nicolò Navarin,Alessandro Sperduti,Davide Anguita
  • Publisher : Springer
  • Release : 02 April 2019
GET THIS BOOKRecent Advances in Big Data and Deep Learning

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

Source Separation and Machine Learning

Source Separation and Machine Learning
  • Author : Jen-Tzung Chien
  • Publisher : Academic Press
  • Release : 01 November 2018
GET THIS BOOKSource Separation and Machine Learning

Source Separation and Machine Learning presents the fundamentals in adaptive learning algorithms for Blind Source Separation (BSS) and emphasizes the importance of machine learning perspectives. It illustrates how BSS problems are tackled through adaptive learning algorithms and model-based approaches using the latest information on mixture signals to build a BSS model that is seen as a statistical model for a whole system. Looking at different models, including independent component analysis (ICA), nonnegative matrix factorization (NMF), nonnegative tensor factorization (NTF), and

Biometrics—Advances in Research and Application: 2013 Edition

Biometrics—Advances in Research and Application: 2013 Edition
  • Author : Anonim
  • Publisher : ScholarlyEditions
  • Release : 21 June 2013
GET THIS BOOKBiometrics—Advances in Research and Application: 2013 Edition

Biometrics—Advances in Research and Application: 2013 Edition is a ScholarlyBrief™ that delivers timely, authoritative, comprehensive, and specialized information about ZZZAdditional Research in a concise format. The editors have built Biometrics—Advances in Research and Application: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about ZZZAdditional Research in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Biometrics—Advances in Research

Advances in Machine Learning and Signal Processing

Advances in Machine Learning and Signal Processing
  • Author : Ping Jack Soh,Wai Lok Woo,Hamzah Asyrani Sulaiman,Mohd Azlishah Othman,Mohd Shakir Saat
  • Publisher : Springer
  • Release : 18 June 2016
GET THIS BOOKAdvances in Machine Learning and Signal Processing

This book presents important research findings and recent innovations in the field of machine learning and signal processing. A wide range of topics relating to machine learning and signal processing techniques and their applications are addressed in order to provide both researchers and practitioners with a valuable resource documenting the latest advances and trends. The book comprises a careful selection of the papers submitted to the 2015 International Conference on Machine Learning and Signal Processing (MALSIP 2015), which was held on 15–17 December 2015

Advances in Principal Component Analysis

Advances in Principal Component Analysis
  • Author : Ganesh R. Naik
  • Publisher : Springer
  • Release : 11 December 2017
GET THIS BOOKAdvances in Principal Component Analysis

This book reports on the latest advances in concepts and further developments of principal component analysis (PCA), addressing a number of open problems related to dimensional reduction techniques and their extensions in detail. Bringing together research results previously scattered throughout many scientific journals papers worldwide, the book presents them in a methodologically unified form. Offering vital insights into the subject matter in self-contained chapters that balance the theory and concrete applications, and especially focusing on open problems, it is essential

Advances in Web-Based Learning

Advances in Web-Based Learning
  • Author : Joseph Fong,Chu Ting Cheung,Hong Va Leong,Qing Li
  • Publisher : Springer
  • Release : 02 August 2003
GET THIS BOOKAdvances in Web-Based Learning

This book constitutes the refereed proceedings of the First International Conference on Web-Based Learning, ICWL 2002, held in Hong Kong, China in August 2002.The 34 revised full papers presented together with an invited keynote paper were carefully reviewed and selected from 75 submissions. The papers are organized in topical sections on system modeling and architectures, distance learning systems engineering, collaborative systems, experiences in distance learning, databases and data mining, and multimedia.

Blind Source Separation

Blind Source Separation
  • Author : Ganesh R. Naik,Wenwu Wang
  • Publisher : Springer
  • Release : 21 May 2014
GET THIS BOOKBlind Source Separation

Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). The book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications. Furthermore, the research results previously scattered in many journals and conferences worldwide are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers, R&D engineers and graduate students in

Advances in Financial Machine Learning

Advances in Financial Machine Learning
  • Author : Marcos Lopez de Prado
  • Publisher : John Wiley & Sons
  • Release : 23 January 2018
GET THIS BOOKAdvances in Financial Machine Learning

Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods;

Audio Source Separation and Speech Enhancement

Audio Source Separation and Speech Enhancement
  • Author : Emmanuel Vincent,Tuomas Virtanen,Sharon Gannot
  • Publisher : John Wiley & Sons
  • Release : 22 October 2018
GET THIS BOOKAudio Source Separation and Speech Enhancement

Learn the technology behind hearing aids, Siri, and Echo Audio source separation and speech enhancement aim to extract one or more source signals of interest from an audio recording involving several sound sources. These technologies are among the most studied in audio signal processing today and bear a critical role in the success of hearing aids, hands-free phones, voice command and other noise-robust audio analysis systems, and music post-production software. Research on this topic has followed three convergent paths, starting

Advances in Intelligent Signal Processing and Data Mining

Advances in Intelligent Signal Processing and Data Mining
  • Author : Petia Georgieva,Lyudmila Mihaylova,Lakhmi C Jain
  • Publisher : Springer
  • Release : 27 July 2012
GET THIS BOOKAdvances in Intelligent Signal Processing and Data Mining

The book presents some of the most efficient statistical and deterministic methods for information processing and applications in order to extract targeted information and find hidden patterns. The techniques presented range from Bayesian approaches and their variations such as sequential Monte Carlo methods, Markov Chain Monte Carlo filters, Rao Blackwellization, to the biologically inspired paradigm of Neural Networks and decomposition techniques such as Empirical Mode Decomposition, Independent Component Analysis and Singular Spectrum Analysis. The book is directed to the research

Independent Component Analysis

Independent Component Analysis
  • Author : Te-Won Lee
  • Publisher : Springer Science & Business Media
  • Release : 17 April 2013
GET THIS BOOKIndependent Component Analysis

Independent Component Analysis (ICA) is a signal-processing method to extract independent sources given only observed data that are mixtures of the unknown sources. Recently, blind source separation by ICA has received considerable attention because of its potential signal-processing applications such as speech enhancement systems, telecommunications, medical signal-processing and several data mining issues. This book presents theories and applications of ICA and includes invaluable examples of several real-world applications. Based on theories in probabilistic models, information theory and artificial neural networks,