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Advances in Independent Component Analysis and Learning Machines

of independent component analysis, and its influence in important areas such as statistical signal processing, pattern recognition and deep learning

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Mathematical Analysis For Machine Learning And Data Mining

This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The;

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Machine Learning for Future Fiber-Optic Communication Systems

-maximization (EM) algorithm, principal component analysis (PCA), independent component analysis (ICA), reinforcement learning, and more Covers;

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Intelligent Computing Theories and Application

learning and data analysis for medical and engineering applications; evolutionary computation and learning; independent component analysis;

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Intelligent Computing Theories and Application

learning and data analysis for medical and engineering applications; evolutionary computation and learning; independent component analysis;

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Intelligent Computing Methodologies

learning and data analysis for medical and engineering applications; evolutionary computation and learning; independent component analysis;

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Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis

Classification Techniques for Medical Image Analysis and Computer Aided Diagnosis covers the most current advances on how to apply;

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Machine Learning Algorithms

libraries, such as scikit-learn, NLTK, TensorFlow, and Keras. You will discover new topics such as principal component analysis (PCA), independent;

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Independent Component Analysis

Independent Component Analysis (ICA) has recently become an important tool for modelling and understanding empirical datasets. It is a;

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Intelligent Computing Methodologies

Web Applications; Fuzzy Theory and Algorithms; Supervised Learning; Unsupervised Learning; Kernel Methods and Supporting Vector Machines;

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Neural Networks and Statistical Learning

published results and includes six new chapters that correspond to the recent advances in computational learning theory, sparse coding, deep;

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Regularization, Optimization, Kernels, and Support Vector Machines

learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex;

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Regularization, Optimization, Kernels, and Support Vector Machines

learning, providing a single multidisciplinary source for the latest research and advances in regularization, sparsity, compressed sensing, convex;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Density Ratio Estimation in Machine Learning

, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation;

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Sequential Logic

: Analysis and Synthesis offers a thorough exposition of the analysis and synthesis of both synchronous and asynchronous sequential machines;

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Independent Component Analysis

A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new;

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Introduction Support Vector Machines

This is the first comprehensive introduction to Support Vector Machines (SVMs), a generation learning system based on recent advances;

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Data-Variant Kernel Analysis

techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) * Develops group kernel analysis with;

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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Mathematics for Machine Learning

central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For;

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Growing Adaptive Machines

research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to;

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Advances in Psychology Research

closing study, an analysis of five qualifying works of a psychiatrist on the subject of organizational and methodological component is carried out;

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On Statistical Pattern Recognition in Independent Component Analysis Mixture Modelling

component analysis mixture modelling (ICAMM). This thesis defines a novel formalism for pattern recognition and classification based on ICAMM, which;

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Innovations in Intelligent Machines -2

in Springer SCI Series Volume 70 by including the possible and successful applications of computational intelligence paradigms in machines for;

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Inhuman Power

Artificial Intelligence (AI) has seen major advances in recent years. While machines were always central to the Marxist analysis;

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Inhuman Power

Artificial Intelligence (AI) has seen major advances in recent years. While machines were always central to the Marxist analysis;

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