ABSTRACT: Mathematical optimization is a fundamental aspect of machine learning (ML). An ML task can be conceptualized as optimizing a specific objective using the training dataset to discern patterns ...

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 ...

INNOptimizer is using latest Bayesian Optimization algorithms and a broad set of analytical tools to guide optimizations with minimum experimentation needed. Don't waste time and money with poor ...

Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...

1 Department of Mechanical and Process Engineering (D-MAVT), Eidgenössische Technische Hochschule (ETH) Zürich, Zürich, Switzerland 2 CREATE Lab, École Polytechnique Fédérale de Lausanne (EPFL), ...

Department of Engineering, University of Cambridge, Cambridge CB2 1CB2 1PZ, U.K.

Abstract: Controller tuning and parameter optimization are crucial in system design to improve closed-loop system performance. Bayesian optimization has been established as an efficient model-free ...

EarthArxiv preprint now available https://doi.org/10.31223/X57T5R! ADCIRC forcing and processing. Some generic mesh processing. Assumes gradient wind reduction factor ...

Tecnologico de Monterrey, Institute of Advanced Materials for Sustainable Manufacturing, Ave. Eugenio Garza Sada 2501, Monterrey, Nuevo León 64849, Mexico ...