Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

They used a multi-objective Bayesian optimization machine learning algorithm, which specializes in comparing multiple outcomes and finding the best solution for a problem.

Predictive Model of Objective Response to Nivolumab Monotherapy for Advanced Renal Cell Carcinoma by Machine Learning Using Genetic and Clinical Data: The SNiP-RCC Study. If you have the appropriate ...

Controlling machine learning in a finance environment requires stakeholders' commitment to creating a strong ethical foundation.

In the second part of the analysis, three machine learning models—Logistic Regression, Random Forest, and XGBoost—were implemented for predictive performance. Logistic Regression outperformed others ...

Using a multi-objective Bayesian optimization (MBO) algorithm trained on finite element analysis (FEA) datasets to identify the best candidate nanostructures, the researchers then brought the ...

The researchers collaborated with a team in South Korea, and applied what's known as the multi-objective Bayesian optimization machine learning algorithm.

To overcome these hurdles, researchers turned to Bayesian optimization, a form of machine learning that excels at finding the best possible design among countless options.

The researchers used a multi-objective Bayesian optimization machine learning algorithm to predict optimal geometries for enhancing stress distribution and improving the strength-to-weight ratio ...