Machine learning is reshaping the way portfolios are built, monitored, and adjusted. Investors are no longer limited to ...

Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...

Machine learning (ML) is rapidly emerging as a powerful tool to improve the safety, reliability, and long-term performance of marine structures exposed to harsh ocean environments. This study presents ...

However, NGD faces several challenges associated with gamma-ray generation and attenuation complexities. Unlike GGD, which utilizes 0.662 MeV monoenergetic γ rays from a 137 Cs source, NGD employs ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

There was an error while loading. Please reload this page. In this notebook, we're going to go through an example machine learning project to use the characteristics ...

Hyperparameter tuning is critical to the success of cross-device federated learning applications. Unfortunately, federated networks face issues of scale, heterogeneity, and privacy; addressing these ...

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 ...

Start a Ray head node Connect and start Ray worker nodes via SSH Activate virtual environments and configure PYTHONPATH on all nodes 📌 Before running the script, ensure passwordless SSH access from ...