Bayesian optimization is a method used to optimize complex functions that are expensive or time-consuming to evaluate. It is widely applied in machine learning, engineering, and scientific research to improve efficiency and precision, particularly in scenarios like hyperparameter tuning and experimental design. ✔️ Efficient Function Evaluation: Bayesian optimization minimizes costly evaluations, making it ideal for scenarios where each evaluation has a high resource cost. ✔️ Versatility: It hand

Self-Tuning Networks: Amortizing the Hypergradient Computation for Hyperparameter Optimization

Automatic Hyperparameter Tuning - A Visual Guide (Part 1) | Antonin Raffin | Homepage

Hyperparameter Optimization for Machine Learning

Hyperparameter Optimization (HPO) on Microsoft AzureML using RAPIDS and NVIDIA GPUs