Scientific Research Publishing

Enhanced Liver Tumor Detection in CT Images Using 3D U-Net and Bat Algorithm for Hyperparameter Optimization ()

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, ...
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 ...
marktechpost

Alibaba Introduces Group Sequence Policy Optimization (GSPO): An Efficient Reinforcement Learning Algorithm that Powers the Qwen3 Models

Reinforcement learning (RL) plays a crucial role in scaling language models, enabling them to solve complex tasks such as competition-level mathematics and programming through deeper reasoning.
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 ...
Frontiers

Machine learning prediction and interpretability analysis of high-risk chest pain: a study from the MIMIC-IV database

Background: High-risk chest pain is a critical presentation in emergency departments, frequently indicative of life-threatening cardiopulmonary conditions. Rapid and accurate diagnosis is pivotal for ...
Scientific Research Publishing

Snoek, J., Larochelle, H. and Adams, R.P. (2012) Practical Bayesian Optimization of Machine Learning Algorithms. arXiv: 1206.2944.

ABSTRACT: The rapid proliferation of the Internet of Things (IoT) and Industrial IoT (IIoT) has revolutionized industries through enhanced connectivity and automation. However, this expansion has ...
Frontiers

Optimized prediction of diabetes complications using ensemble learning with Bayesian optimization: a cost-efficient laboratory-based approach

Background and objective: The increasing global prevalence of diabetes has led to a surge in complications, significantly burdening healthcare systems and affecting patient quality of life. Early ...
IEEE

A Comparative Study of Hyperparameter Tuning in Deep Learning Models using Bayesian Optimization and XAI

Abstract: Plant disease detection is a crucial step in improving the quantity and quality of farm products since many plant diseases that arise in rice crops reduce the production of agriculture and ...