Frontiers

Hybrid intelligent systems for liver disease prediction: a demographic-aware machine learning framework

Background: Liver disease remains a major global health burden, often progressing undetected until advanced stages. Traditional diagnostic approaches, while accurate, are invasive, costly, and limited ...
Search Engine Land

How Bayesian testing lets Google measure incrementality with $5,000

Incrementality testing in Google Ads is suddenly within reach for far more advertisers than before. Google has lowered the barriers to running these tests, making lift measurement possible even ...
IEEE

Enhancing Privacy-Preserved Iris Recognition in Consumer Electronics: A Soft Actor-Critic and GAN-Based Digital Forensic Framework With Bayesian Hyperparameter Optimization

Abstract: The widespread deployment of iris recognition (IR) systems in consumer electronics has raised pressing concerns related to digital forensics, biometric integrity, and user privacy. This ...
Search Engine Land

What is LLMO? Optimize content for AI & large language models

Chances are, you’ve seen clicks to your website from organic search results decline since about May 2024—when AI Overviews launched. Large language model optimization (LLMO), a set of tactics for ...
Frontiers

Explainable machine learning for early detection of Parkinson’s disease in aging populations using vocal biomarkers

1 Department of Electrical and Computer Engineering, School of Engineering and Digital Sciences, Nazarbayev University, Astana, Kazakhstan 2 School of Information Technology and Systems, University of ...
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

Automated Class Imbalance Learning via Few-shot Multi-Objective Bayesian Optimization with Deep Kernel Gaussian Processes

Abstract: Automated Class Imbalance Learning (AutoCIL) is an emerging paradigm that leverages Combined Algorithm Selection and Hyperparameter Optimization (CASH) to automate the configuration of ...
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 ...