PC World

This Windows feature secretly eats up RAM and slows your PC over time

PCWorld reports that Windows’ Delivery Optimization feature, designed for update sharing between computers, can unexpectedly consume significant amounts of RAM over time. Reddit user testing confirmed ...
Scientific Research Publishing

Snoek, J., Larochelle, H. and Adams, R.P. (2012) Practical Bayesian Optimization of Machine Learning Algorithms. Advances in Neural Information Processing Systems, Vol. 5, 2951 ...

ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
C&EN

Kβ X-ray Emission Spectra Analysis Using Bayesian Optimization

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 ...
GitHub

An AutoML framework for classical machine learning algorithms, automating model selection and hyperparameter tuning through Bayesian optimization, portfolio-based meta-learning ...

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 ...
IEEE

Hyperparameter Tuning of LSTM Load Forecasting Model Based on Segmented Bayesian Optimization

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 ...
GitHub

[FR] Native Bayesian Hyperparameter Optimization Integration

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 ...
IEEE

Efficient Deep Learning Hyperparameter Tuning Using Cloud Infrastructure: Intelligent Distributed Hyperparameter Tuning with Bayesian Optimization in the Cloud

Abstract: The paper discusses how we can leverage cloud infrastructure for efficient hyperparameter tuning of deep neural networks on high dimensional hyperparameter spaces using Bayesian Optimization ...