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Dictionary Learning Algorithms and Applications

This book covers all the relevant dictionary learning algorithms, presenting them in full detail and showing their distinct characteristics;

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Machine Learning Theoretical Foundations and Practical Applications

in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network;

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Learning Algorithms

the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms;

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Deep Learning: Algorithms and Applications

This book presents a wealth of deep-learning algorithms and demonstrates their design process. It also highlights the need for a prudent;

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Algorithms in Machine Learning Paradigms

, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence;

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Algorithms in Machine Learning Paradigms

, feature extraction-based learning, optimization-based learning, quantum-inspired learning, multi-criteria-based learning and hybrid intelligence;

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Machine Learning with SAP

Work smarter with machine learning! Begin with core machine learning concepts-types of learning, algorithms, data preparation, and more;

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Machine Learning and Metaheuristics Algorithms, and Applications

This book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications;

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Brain and Nature-Inspired Learning, Computation and Recognition

Brain and Nature-Inspired Learning, Computation and Recognition presents a systematic analysis of neural networks, natural computing;

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Artificial Intelligence Algorithms and Applications

control, big data and cloud computing, deep learning, and hybrid machine learning systems.The papers are organized according to the following;

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Nature-Inspired Computation in Data Mining and Machine Learning

mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their;

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Nature-Inspired Computation in Data Mining and Machine Learning

mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their;

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Unsupervised Learning Algorithms

of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained;

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Machine Learning and Big Data

learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent;

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Introduction to Deep Learning Business Applications for Developers

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples;

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Hands-On Genetic Algorithms with Python

Explore the ever-growing world of genetic algorithms to solve search, optimization, and AI-related tasks, and improve machine learning;

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Online Visual Tracking

methods based on online learning algorithms, including sparse representation, dictionary learning, hashing codes, local model, and model fusion;

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Image Understanding Using Sparse Representations

kernelizing the sparse coding and dictionary learning methods are presented. In addition to presenting theoretical fundamentals in sparse learning;

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Sparse Modeling

dictionary learning and sparse matrix factorizations.;

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Sparse Modeling

models and cover dictionary learning and sparse matrix factorizations.;

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Kernel Learning Algorithms for Face Recognition

kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and;

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Neural Fuzzy Control Systems With Structure And Parameter Learning

author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised;

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Computational Learning Approaches to Data Analytics in Biomedical Applications

using varied machine learning and statistical techniques. It presents insights on biomedical data processing, innovative clustering algorithms;

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Algorithmic Advances in Riemannian Geometry and Applications

methods, and dictionary learning and sparse coding on manifolds. Examples of applications include novel algorithms for Monte Carlo sampling and;

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Self-Learning and Adaptive Algorithms for Business Applications

with the help of traditional techniques. Self-learning and adaptive algorithms are now widely used by such leading giants that as Google, Tesla;

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Machine Learning The New AI

systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product;

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Machine Learning and Metaheuristics Algorithms and Applications

This book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications;

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