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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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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 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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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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Alternating Direction Method of Multipliers for Machine Learning

linearly constrained ones. Written by experts in machine learning and optimization, this is the first book providing a state-of-the-art review on;

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Optimization for Data Analysis

Optimization techniques are at the core of data science, including data analysis and machine learning. An understanding of basic;

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Introduction To Stochastic Search And Optimization

A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast;

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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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Stochastic Optimization with Simulation Based Optimization

Stochastic optimization is vital to making sound engineering and business decisions under uncertainty. While the limited capability;

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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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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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Machine Learning for Networking: First International Conference, Mln 2018, Paris, France, November 27-29, 2018, Revised Selected Papers

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

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Adaptive Stochastic Optimization Techniques with Applications

Adaptive Stochastic Optimization Techniques with Applications provides a single, convenient source for state-of-the-art information on;

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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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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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Learning and Intelligent Optimization

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

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Stochastic Optimization Methods: Applications in Engineering and Operations Research

differentiation formulas for probabilities and expectations. In the third edition, this book further develops stochastic optimization methods;

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Theory of Information and its Value

, progress in machine learning, artificial intelligence algorithms, and increased computational resources, the need for comprehending information;

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Optimization in Machine Learning and Applications

from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which;

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Optimization in Machine Learning and Applications

from multimodal data. It discusses the optimization methods that help minimize the error in developing patterns and classifications, which;

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High-Performance Simulation-Based Optimization

This book presents the state of the art in designing high-performance algorithms that combine simulation and optimization in order to solve;

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