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: Bayesian optimization is commonly used to optimize black-box functions associated with simulations in engineering and science. Bayesian optimization contains two essential components: the ...

Abstract: As awareness of data privacy protection continues to grow, many-task optimization faces a significant challenge in balancing privacy protection and performance improvement. This paper ...

Peter the Great St. Petersburg Polytechnic University, St. Petersburg 195251, Russian Federation Academic University, Russian Academy of Sciences, St. Petersburg 194021, Russian Federation ...

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 ...

1 State Key Laboratory of Geohazard Prevention and Geoenvironment Protection, Chengdu University of Technology, Chengdu, China 2 State Key Laboratory of Mountain Bridge and Tunnel Engineering, ...

This repository contains experiment that implements Bayesian Optimization (BO) techniques for Conditional Value-at-Risk (CVaR)-based portfolio optimization, inspired by the research paper "Bayesian ...

Accurate disaster prediction combined with reliable uncertainty quantification is crucial for timely and effective decision-making in emergency management. However, traditional deep learning methods ...