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Open Problems in Optimization and Data Analysis

Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain;

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Post-Optimal Analysis in Linear Semi-Infinite Optimization

optimization: modeling uncertainty, qualitative stability analysis, quantitative stability analysis and sensitivity analysis. Linear semi-infinite;

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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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Multivariate Data Analysis on Matrix Manifolds

include computational statistics, data analysis, data mining and data science, as well as theoretical computer science, machine learning and;

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Nature Inspired Computing for Data Science

optimization techniques. Focusing on various data science problems, including classification, clustering, forecasting, and deep learning, it explores;

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Optimization Problems in Graph Theory

This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications;

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Optimization Problems and Their Applications

in data analysis, mathematical programming, game theory and economical applications, applied optimization problems and metaheuristics.;

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Swarm Intelligence Methods for Statistical Regression

overview of statistical data analysis and key results in stochastic optimization theory Focuses on methodology and results rather;

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Swarm Intelligence Methods for Statistical Regression

of statistical data analysis and key results in stochastic optimization theory Focuses on methodology and results rather than formal proofs;

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Mathematical Modeling and Optimization of Complex Structures

design problems in science and engineering; * Sensitivity analysis and parameters optimization of complex systems.;

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Data Envelopment Analysis with R

data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how;

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Data Envelopment Analysis with R

data envelopment analysis (DEA), with a special emphasis on fuzzy DEA. It then describes DEA models, including fuzzy DEA models, and shows how;

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Data Correcting Approaches in Combinatorial Optimization

Data Correcting Approaches in Combinatorial Optimization focuses on algorithmic applications of the well known polynomially solvable;

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Optimization and Control for Systems in the Big-Data Era

This book focuses on optimal control and systems engineering in the big data era. It examines the scientific innovations in optimization;

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Recent Advances In Stochastic Modeling And Data Analysis

This volume presents the most recent applied and methodological issues in stochastic modeling and data analysis. The contributions cover;

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Optimization and Applications

problems of operations research, data analysis, and software development.;

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Aerospace System Analysis and Optimization in Uncertainty

modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range;

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Aerospace System Analysis and Optimization in Uncertainty

modeling, sensitivity analysis, uncertainty propagation, reliability analysis, and global multidisciplinary optimization. The extensive range;

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Multi-Objective Optimization utilizing Cluster Analysis applied to Dimensional Transposed Problems

With respect to the importance of multi-objective optimization in the context of the today's information processing and analysis, as well;

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Optimization Methods in Metabolic Networks

Provides a tutorial on the computational tools that use mathematical optimization concepts and representations for the curation, analysis;

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Optimal Structural Design

(guaranteed) optimization approaches with incomplete data. The book presents analytical and numerical results developed by the authors during the last;

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Statistical Inference via Convex Optimization

essential resource for optimization specialists who are new to statistics and its applications, and for data scientists who want to improve their;

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Nonlinear Analysis and Global Optimization

, optimization models for networks of organ transplants, network curvature measures, error analysis through energy minimization and stability problems;

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Methods for Petroleum Well Optimization

of open-source code which will help companies, engineers, and researchers develop their prediction and analysis software more quickly; this;

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Convexity And Optimization In Rn

understanding of the material. Convexity and Optimization in Rn provides detailed discussion of: Requisite topics in real analysis Convex sets;

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Computational Intelligence in Expensive Optimization Problems

, data mining and statistical analysis, analysis of real-world cases (such as multidisciplinary design optimization). The edited book;

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Classical And Modern Optimization

in mathematics, engineers, data scientists or economists, Classical and Modern Optimization contains more than 200 exercises to assist with self-study or;

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