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SOLO FTRL ALGORITHM FOR PRODUCTION MANAGEMENT WITH TRANSFER PRICES
We consider a firm producing and selling d commodities, and consisting of n production and m sales divisions. The firm manager tries to stimulate the...
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On the Representation and Learning of Monotone Triangular Transport Maps
Transportation of measure provides a versatile approach for modeling complex probability distributions, with applications in density estimation,...
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Sampling-Based Learning Control of Quantum Systems with Uncertainties
This chapter presents results on enhancing robustness of quantum systems with uncertainties using the sampling-based learning control (SLC) method....
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Solute transport prediction in heterogeneous porous media using random walks and machine learning
Solute transport processes in heterogeneous porous media have been traditionally studied through the parameterization of macroscale properties using...
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Q-Learning in Regularized Mean-field Games
In this paper, we introduce a regularized mean-field game and study learning of this game under an infinite-horizon discounted reward function....
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Pre-clustered Generative Adversarial Network Model for Mongolian Font Style Transfer
Font style transfer has important application value in the field of data enhancement and can be used to alleviate the problem of insufficient data in...
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A K-means Supported Reinforcement Learning Framework to Multi-dimensional Knapsack
In this paper, we address the difficulty of solving large-scale multi-dimensional knapsack instances (MKP), presenting a novel deep reinforcement...
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Network flow problem heuristic reduction using machine learning
Most of the supporting tools developed for logistic optimization and processing infrastructure planning are based on the network flow problem. The...
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Flexible job-shop scheduling with limited flexible workers using an improved multiobjective discrete teaching–learning based optimization algorithm
Flexible job-shop scheduling problem with worker flexibility (FJSPW) has been frequently investigated during the last decade. Many real-world...
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Mean-field coupled systems and self-consistent transfer operators: a review
In this review we survey the literature on mean-field coupled maps. We start with the early works from the physics literature, arriving to some...
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Maliciously roaming person's detection around hospital surface using intelligent cloud-edge based federated learning
As an innovative strategy, cloud-edge-based federated learning has been considered a suitable option in supporting applications in the internet of...
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Connections between Robust Statistical Estimation, Robust Decision-Making with Two-Stage Stochastic Optimization, and Robust Machine Learning Problems
The authors discuss connections between the problems of two-stage stochastic programming, robust decision-making, robust statistical estimation, and...
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Optimizing Multimodal Transportation Systems Using the Teaching–Learning-Based Algorithm
Multimodal transportation systems (MTS) represent a cornerstone of modern logistics and transportation planning. At its core, MTS involves...
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Combining Stochastic Models with Machine Learning
Machine learning has become a prevalent and powerful tool in many scientific and engineering disciplines. This last chapter presents a few methods...
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Physically Informed Deep Learning Technique for Estimating Blood Flow Parameters in Arterial Bifurcations
AbstractThis research investigates application of physically regularized deep learning for the estimation of blood flow parameters in bifurcations of...
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MILP Acceleration: A Survey from Perspectives of Simplex Initialization and Learning-Based Branch and Bound
Mixed integer linear programming (MILP) is an NP-hard problem, which can be solved by the branch and bound algorithm by dividing the original problem...
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Generalizing a Secure Framework for Domain Transfer Network for Face Anti-spoofing
An essential field in cyber-security is the technology behind the authentication of users. In the contemporary era, alphanumeric passwords have been...
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Learning to sample initial solution for solving 0–1 discrete optimization problem by local search
Local search methods are convenient alternatives for solving discrete optimization problems (DOPs). These easy-to-implement methods are able to find...
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Access Control Method for EV Charging Stations Based on State Aggregation and Q-Learning
This paper presents intelligent access control for a charging station and a framework for dynamically and adaptively managing charging requests from...
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Learning Invariance Preserving Moment Closure Model for Boltzmann–BGK Equation
As one of the main governing equations in kinetic theory, the Boltzmann equation is widely utilized in aerospace, microscopic flow, etc. Its...
