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Accelerated Optimization for Machine Learning

provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It;

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Accelerated Optimization for Machine Learning

provides a comprehensive introduction to, and state-of-the-art review of accelerated first-order optimization algorithms for machine learning. It;

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Optimization for Data Analysis

fundamental methods in optimization are described and analyzed, including: gradient and accelerated gradient methods for unconstrained optimization;

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Optimization for Machine Learning

An up-to-date account of the interplay between optimization and machine learning, accessible to students and researchers in both;

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Alternating Direction Method of Multipliers for Machine Learning

Machine learning heavily relies on optimization algorithms to solve its learning models. Constrained problems constitute a major type;

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Linear Algebra and Optimization for Machine Learning

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout;

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Linear Algebra and Optimization for Machine Learning

This textbook introduces linear algebra and optimization in the context of machine learning. Examples and exercises are provided throughout;

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Distributed Machine Learning and Gradient Optimization

This book presents the state of the art in distributed machine learning algorithms that are based on gradient optimization methods. In the;

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First-order and Stochastic Optimization Methods for Machine Learning

fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized;

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First-order and Stochastic Optimization Methods for Machine Learning

fundamental concepts and recent progresses on machine learning algorithms, especially on those based on stochastic optimization methods, randomized;

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Machine Learning for Networking

learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection, optimization and new;

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Optinformatics in Evolutionary Learning and Optimization

optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data;

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Optinformatics in Evolutionary Learning and Optimization

optimization. The book also provides readers a variety of practical applications, including inter-domain learning in vehicle route planning, data;

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Machine Learning, Optimization, and Big Data

This book constitutes revised selected papers from the First International Workshop on Machine Learning, Optimization, and Big Data, MOD;

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Machine Learning, Optimization, and Data Science

This book constitutes the post-conference proceedings of the 4th International Conference on Machine Learning, Optimization, and Data;

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Machine Learning, Optimization, and Data Science

This book constitutes the post-conference proceedings of the 5th International Conference on Machine Learning, Optimization, and Data;

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Machine Learning, Optimization, and Big Data

This book constitutes revised selected papers from the Second International Workshop on Machine Learning, Optimization, and Big Data, MOD;

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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

, Optimization, Kernels, and Support Vector Machines is ideal for researchers in machine learning, pattern recognition, data mining, signal processing;

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Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities

This volume offers a wealth of interdisciplinary approaches to artificial intelligence, machine learning and optimization tools, which;

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Learning and Intelligent Optimization

programming, global optimization, machine learning, and artificial intelligence and describe advanced ideas, technologies, methods, and applications;

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Implementations and Applications of Machine Learning

rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining;

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Implementations and Applications of Machine Learning

rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining;

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Learning and Intelligent Optimization

, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced ideas, technologies, methods, and;

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Learning and Intelligent Optimization

interconnected fields as mathematical programming, global optimization, machine learning, and artificial intelligence. Special focus is given to advanced;

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Learning and Intelligent Optimization

This book constitutes the thoroughly refereed post-conference proceedings of the 9th International Conference on Learning and Optimization;

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