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 ...

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 ...

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

An illustration of a magnifying glass. An illustration of a magnifying glass.

1 Department of Mathematics and Statistics, Loyola University Chicago, Chicago, IL, USA. 2 Department of Mathematics and Computer Science, Islamic Azad University, Science and Research Branch, Tehran, ...

Abstract: As a key link in power system operation and planning, the prediction accuracy of power load forecasting is directly related to the economy, security and power supply reliability of power ...

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

1 Department of Biochemistry, Brandeis University, Waltham, MA, United States 2 Department of Biology, Brandeis University, Waltham, MA, United States This study explores the efficacy of Bayesian ...

Add native support for Bayesian hyperparameter optimization directly within MLflow, eliminating the need for external libraries like Optuna or Hyperopt. This feature would provide a deeply integrated ...