IEEE

Application and Effectiveness Evaluation of Bayesian Optimization Algorithm in Hyperparameter Tuning of Machine Learning Models

Abstract: Hyperparameter tuning is a crucial step in the development of machine learning models, as it directly impacts their performance and generalization ability. Traditional methods for ...
GitHub

Umer-Farooq-CS/CNN-CIFAR10-Classification-GPU-Optimized

This project implements a state-of-the-art CNN architecture for CIFAR-10 image classification, achieving 88.82% accuracy through systematic hyperparameter optimization. The implementation includes GPU ...
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, ...
Electronic Design

The Migration of AI from Buzzword to Application Solution

Check out more podcasts in the TechXchange: Inside Electronics Podcast. Artificial intelligence and machine learning (AI/ML) have slowly grown and matured in the industry from being slightly more than ...
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 ...
GitHub

bayesian optimization for hyperparameter tuning

should we consider incorporating bayesian optimization for hyperparameter search? it could be distributed with across different machines, just as with gridsearch, but ...