Titlebook: Machine Learning, Optimization, and Data Science; 8th International Co Giuseppe Nicosia,Varun Ojha,Renato Umeton Conference proceedings 202

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,Local Optimisation of?Nystr?m Samples Through Stochastic Gradient Descent,isets of landmark points in the ambient space; such multisets are referred to as Nystr?m samples. We consider an unweighted variation of the radial squared-kernel discrepancy (SKD) criterion as a surrogate for the classical criteria used to assess the Nystr?m approximation accuracy; in this setting,

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,Intelligent Robotic Process Automation for?Supplier Document Management on?E-Procurement Platforms,sely, different suppliers compete against each other to be selected, by one or more buyers, as those to be commissioned with procuring goods and services. However, such interactions are risky because suppliers may trick buyers by issuing false information about themselves. For this reason, procureme

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Batch Bayesian Quadrature with Batch Updating Using Future Uncertainty Sampling,s is a central problem both within and without machine learning, including model averaging, (hyper-)parameter marginalization, and computing posterior predictive distributions. Recently, Batch Bayesian Quadrature has successfully combined the probabilistic integration techniques of Bayesian Quadratu

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Sensitivity Analysis of Engineering Structures Utilizing Artificial Neural Networks and Polynomial ilized in order to obtain various sensitivity measures of quantity of interest. The artificial neural networks and polynomial chaos expansion are used for efficient sensitivity analysis. Each of the techniques is superior in different areas of uncertainty quantification and thus each of them is used

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,MicroRacer: A Didactic Environment for?Deep Reinforcement Learning,ty of the environment has been explicitly calibrated to allow users to experiment with many different methods, networks and hyperparameters settings without requiring sophisticated software or exceedingly long training times. Baseline agents for major learning algorithms such as DDPG, PPO, SAC, TD3

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,A Practical Approach for?Vehicle Speed Estimation in?Smart Cities,ices to citizens especially related to their safety. This motivation, enabled by the widespread evolution of cutting edge technologies within the Artificial Intelligence, Internet of Things, and Computer Vision, has led to the creation of smart cities. One example of services that different cities a