Not everyone will write their own optimizing compiler from scratch, but those who do sometimes roll into it during the course ...

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

Understand and implement the RMSProp optimization algorithm in Python. Essential for training deep neural networks efficiently. #RMSProp #Optimization #DeepLearning Denmark facing "decisive moment" ...

Abstract: Microwave device design increasingly relies on surrogate modeling to accelerate optimization and reduce costly electromagnetic (EM) simulations. This article presents a spectral Bayesian ...

Mechatronics, high-speed robot design, force- and vision-based machine control, artificial reflexes for autonomous machines, rapid prototyping, agile manufacturing, mobile robotic platforms Marvel, ...

Article subjects are automatically applied from the ACS Subject Taxonomy and describe the scientific concepts and themes of the article. In this paper, we introduce a methodology to improve upon the ...

Synthetic dataset outputs for public analysis without privacy risk. Part of my current workflow as survey leader of the Data Engineering Pilipinas group. Comparable distributions per column: based on ...

This paper investigates the application of machine learning techniques to optimize complex spray-drying operations in manufacturing environments. Using a mixed-methods approach that combines ...

Abstract: Hierarchical clustering is a method in data mining and statistics used to build a hierarchy of clusters. Traditional hierarchical clustering relies on a measure of dissimilarity to combine ...