Pre-Owned Springerbriefs in Optimization Bayesian and High-Dimensional Global Optimization Paperback from other stores

  • Accessible to a variety of readers this book is of interest to specialists gra... Accessible to a variety of readers this book is of interest to specialists graduate students and researchers in mathematics optimization computer science operations research management science engineering and other applied areas interested in... more
  • This volume brings together the main results in the field of Bayesian Optimiza... This volume brings together the main results in the field of Bayesian Optimization (BO) focusing on the last ten years and showing how on the basic framework new methods have been specialized to solve emerging problems from machine learning... more
  • Simplicial Global Optimization is centered on deterministic covering methods p... Simplicial Global Optimization is centered on deterministic covering methods partitioning feasible region by simplices. This book looks into the advantages of simplicial partitioning in global optimization through applications where the search space... more
  • This volume presents extensive research devoted to a broad spectrum of mathema... This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability. Chapters also emphasize applications to Data Science a timely field with a high impact in... more
  • This volume brings together the main results in the field of Bayesian Optimiza... This volume brings together the main results in the field of Bayesian Optimization (BO) focusing on the last ten years and showing how on the basic framework new methods have been specialized to solve emerging problems from machine learning... more
  • This book introduces in an accessible way the basic elements of Numerical PDE-... This book introduces in an accessible way the basic elements of Numerical PDE-Constrained Optimization from the derivation of optimality conditions to the design of solution algorithms. Numerical optimization methods in function-spaces and their... more
  • Polynomial optimization have been a hot research topic for the past few years ... Polynomial optimization have been a hot research topic for the past few years and its applications range from Operations Research biomedical engineering investment science to quantum mechanics linear algebra and signal processing among many others.... more
  • This focused monograph presents a study of subgradient algorithms for constrai... This focused monograph presents a study of subgradient algorithms for constrained minimization problems in a Hilbert space. The book is of interest for experts in applications of optimization to engineering and economics. The goal is to obtain a... more
  • This volume presents extensive research devoted to a broad spectrum of mathema... This volume presents extensive research devoted to a broad spectrum of mathematics with emphasis on interdisciplinary aspects of Optimization and Probability. Chapters also emphasize applications to Data Science a timely field with a high impact in... more
  • Introduction to Global Optimization Exploiting Space-Filling Curves provides a... Introduction to Global Optimization Exploiting Space-Filling Curves provides an overview of classical and new results pertaining to the usage of space-filling curves in global optimization. The authors look at a family of derivative-free numerical... more
  • Simplicial Global Optimization is centered on deterministic covering methods p... Simplicial Global Optimization is centered on deterministic covering methods partitioning feasible region by simplices. This book looks into the advantages of simplicial partitioning in global optimization through applications where the search space... more
  • Latent factor analysis models are an effective type of machine learning model ... Latent factor analysis models are an effective type of machine learning model for addressing high-dimensional and sparse matrices which are encountered in many big-data-related industrial applications. The performance of a latent factor analysis... more
  • This book examines geometric branch-and-bound methods such as in Lipschitzian ... This book examines geometric branch-and-bound methods such as in Lipschitzian optimization d.c. programming and interval analysis introduces a new concept for the rate of convergence and also analyzes several bounding operations reported in the... more
  • This book presents basic optimization principles and gradient-based algorithms... This book presents basic optimization principles and gradient-based algorithms to a general audience in a brief and easy-to-read form without neglecting rigor. The text is structured to let professionals apply optimization theory and algorithms to... more
  • This brief provides an elementary introduction to the theory of piecewise diff... This brief provides an elementary introduction to the theory of piecewise differentiable functions with an emphasis on differentiable equations. In the first chapter two sample problems are used to motivate the study of this theory. The presentation... more
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