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Book Synopsis

Application of Machine Learning to Increase the Efficiency of the Global Search Algorithm for Solving Multicriterial Problems.- Sequential Decision Modeling for Dynamic Pricing and Revenue Management in Hotels.- Resource Allocation via Bayesian Optimization: An Efficient Alternative to Semi-Bandit Feedback.- Multi-Objective and Multiple Information Source Optimization for Fair & Green Machine Learning.- Extended Optimal Control Problem for Practical Application.- Explainable Process Deviance Discovery with Data-Efficient Deep Learning.- Line Search Stochastic Gradient Algorithm with a-Priori Rule for Monitoring the Control of the Variance.- A Machine Learning Approach to Speed up the Solution of the Distributor's Pallet Loading Problem.- Combined First- and Second-Order Directions for Deep Neural Networks Training.- Constrained Global Optimization by Smoothing.- The Unreasonable Effectiveness of Optimal Transport Distance in the Design of Multi-Objective Evolutionary Optimization Algorithms.- An Improved Modified Jaya Optimization Algorithm: Application to the Solution of Nonlinear Equation Systems.- GPU Acceleration of the Enhanced Jaya Optimization Algorithm for Solving Large Systems of Nonlinear Equations.- Effective Resistance Based Community Detection in Complex Networks.- A Comparison of Formulations for Aircraft Deconfliction.- Optimal Recombination Problem in Genetic Programming for Boolean Functions.- Heuristics with Local Improvements for Two-Processor Scheduling Problem with Energy Constraint and Parallelization.- Numerical Analysis of Optimal Control of Assets and Liabilities by a Bank.- Optimal Control for Stochastic Multi-Agent Systems with the Use of Parallel Hybrid Genetic Algorithm.- DC Optimization in Adversarial Support Vector Machine.- A First-Order Optimality Condition in Nonsmooth Generalized Semi-Infinite Programming (GSIP).- Miniaturisation of Binary Classifiers through Sparse Neural Networks.- Price Forecasting for Bitcoin: Linear Regression and SVM Approaches.- Inside the Box: 0-1 Linear Programming under Interval Uncertainty.- Machine Learning Techniques for Branch-and-Cut Methods: The Selection of Cutting Planes.- The Critical Cone and Second-Order Optimality Conditions for a State-Constrained Optimal Control Problem.- Local Information in Global Optimization with Dimensionality Reduction Schemes.- A Heuristic Solution Approach for Bulk Port Routing Optimization.- A Genetic Algorithm to Optimize the Dispatch of Firefighting Resources.- Robust Non-Convex Model-Based Approach for Deep Learning-Based Image Processing.- A DCA-Like Based Algorithm for the Merkle Tree Construction Problem in Ethereum Cryptocurrency System.- Numerical Optimization in Hyperbolic Space - Applications to Drug-Target Interaction Prediction.- Improving Feasibility of Optimal Control via Obtaining High-precision Model.- Dimensionality Reduction for Quadratic Convex Maximization.- Population Local Search for Single Processor Energy Efficient Scheduling Problem.

Numerical Computations Theory and Algorithms

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    A Paperback by Yaroslav D. Sergeyev

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      Publisher: Springer
      Publication Date: Publication Date: 01/01/2025
      ISBN13: 9783031812408, 978-3031812408
      ISBN10:
      Also in:
      Computing Maths for computer scientists

      Description

      Book Synopsis

      Application of Machine Learning to Increase the Efficiency of the Global Search Algorithm for Solving Multicriterial Problems.- Sequential Decision Modeling for Dynamic Pricing and Revenue Management in Hotels.- Resource Allocation via Bayesian Optimization: An Efficient Alternative to Semi-Bandit Feedback.- Multi-Objective and Multiple Information Source Optimization for Fair & Green Machine Learning.- Extended Optimal Control Problem for Practical Application.- Explainable Process Deviance Discovery with Data-Efficient Deep Learning.- Line Search Stochastic Gradient Algorithm with a-Priori Rule for Monitoring the Control of the Variance.- A Machine Learning Approach to Speed up the Solution of the Distributor's Pallet Loading Problem.- Combined First- and Second-Order Directions for Deep Neural Networks Training.- Constrained Global Optimization by Smoothing.- The Unreasonable Effectiveness of Optimal Transport Distance in the Design of Multi-Objective Evolutionary Optimization Algorithms.- An Improved Modified Jaya Optimization Algorithm: Application to the Solution of Nonlinear Equation Systems.- GPU Acceleration of the Enhanced Jaya Optimization Algorithm for Solving Large Systems of Nonlinear Equations.- Effective Resistance Based Community Detection in Complex Networks.- A Comparison of Formulations for Aircraft Deconfliction.- Optimal Recombination Problem in Genetic Programming for Boolean Functions.- Heuristics with Local Improvements for Two-Processor Scheduling Problem with Energy Constraint and Parallelization.- Numerical Analysis of Optimal Control of Assets and Liabilities by a Bank.- Optimal Control for Stochastic Multi-Agent Systems with the Use of Parallel Hybrid Genetic Algorithm.- DC Optimization in Adversarial Support Vector Machine.- A First-Order Optimality Condition in Nonsmooth Generalized Semi-Infinite Programming (GSIP).- Miniaturisation of Binary Classifiers through Sparse Neural Networks.- Price Forecasting for Bitcoin: Linear Regression and SVM Approaches.- Inside the Box: 0-1 Linear Programming under Interval Uncertainty.- Machine Learning Techniques for Branch-and-Cut Methods: The Selection of Cutting Planes.- The Critical Cone and Second-Order Optimality Conditions for a State-Constrained Optimal Control Problem.- Local Information in Global Optimization with Dimensionality Reduction Schemes.- A Heuristic Solution Approach for Bulk Port Routing Optimization.- A Genetic Algorithm to Optimize the Dispatch of Firefighting Resources.- Robust Non-Convex Model-Based Approach for Deep Learning-Based Image Processing.- A DCA-Like Based Algorithm for the Merkle Tree Construction Problem in Ethereum Cryptocurrency System.- Numerical Optimization in Hyperbolic Space - Applications to Drug-Target Interaction Prediction.- Improving Feasibility of Optimal Control via Obtaining High-precision Model.- Dimensionality Reduction for Quadratic Convex Maximization.- Population Local Search for Single Processor Energy Efficient Scheduling Problem.

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