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Black Box Optimization, Machine Learning, and No-Free Lunch Theorems

This edited volume illustrates the connections between machine learning techniques, black box optimization, and no-free lunch theorems;

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First-order and Stochastic Optimization Methods for Machine Learning

algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the;

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First-order and Stochastic Optimization Methods for Machine Learning

algorithms, nonconvex optimization, distributed and online learning, and projection free methods. This book will benefit the broad audience in the;

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Introduction To Machine Learning In Quantitative Finance, An

well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you;

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Introduction To Machine Learning In Quantitative Finance, An

well as hands-on experience. After reading An Introduction to Machine Learning in Quantitative Finance, ML tools will not be a black box to you;

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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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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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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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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Accelerated Optimization for Machine Learning

This book on optimization includes forewords by Michael I. Jordan, Zongben Xu and Zhi-Quan Luo. Machine learning relies heavily on;

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Bioinspired Heuristics for Optimization

This book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some;

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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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A Brief Introduction to Continuous Evolutionary Optimization

Practical optimization problems are often hard to solve, in particular when they are black boxes and no further information about the;

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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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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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Linear Algebra and Optimization with Applications to Machine Learning - Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied;

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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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Learning and Intelligent Optimization

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

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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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Black Box Simulation Optimization

-making problems. Response Surface Methodology (RSM) is a black box simulation optimization method with its origin in the 1950's. Being a black;

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General-Purpose Optimization Through Information Maximization

Heuristics, the author covers all iterative optimization methods and not just evolutionary methods. The No Free Lunch Theorem is viewed as a useful;

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General-Purpose Optimization Through Information Maximization

Heuristics, the author covers all iterative optimization methods and not just evolutionary methods. The No Free Lunch Theorem is viewed as a useful;

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Machine Learning, Optimization, and Data Science

in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a;

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Machine Learning, Optimization, and Data Science

in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a;

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