🏠 Home
Benchmark Hub
📊 All Benchmarks 🦖 Dinosaur v1 🦖 Dinosaur v2 ✅ To-Do List Applications 🎨 Creative Free Pages 🎯 FSACB - Ultimate Showcase 🌍 Translation Benchmark
Models
🏆 Top 10 Models 🆓 Free Models 📋 All Models ⚙️ Kilo Code
Resources
💬 Prompts Library 📖 AI Glossary 🔗 Useful Links

AI Glossary

The complete dictionary of Artificial Intelligence

162
categories
2,032
subcategories
23,060
terms
📖
terms

Upper Confidence Bound (UCB)

Acquisition function that adds an exploration term, proportional to the model's uncertainty, to the predicted mean, allowing explicit control of the exploration-exploitation trade-off via a parameter.

📖
terms

Probability of Improvement (PI)

Acquisition function that calculates the probability that a candidate point will improve the current best result, tending to favor exploitation of areas already known to be promising.

📖
terms

Kernel (or Covariance Function)

Function that defines the similarity between two points in the search space and determines the smoothing properties of the Gaussian process, crucial for the quality of the surrogate model.

📖
terms

Multi-Objective Optimization

Extension of Bayesian optimization aimed at simultaneously optimizing multiple conflicting objectives, producing a Pareto front of non-dominated solutions.

📖
terms

Parallel Optimization

Variant of Bayesian optimization that proposes multiple points to evaluate simultaneously, accelerating the process by leveraging distributed computing resources.

📖
terms

Kernel Hyperparameter

Parameters of the Gaussian process kernel (such as length scale or variance) that define the correlation structure of the surrogate model and are often optimized internally.

📖
terms

Latin Hypercube Sampling Initialization

Strategy for generating the first evaluation points that ensures homogeneous coverage of the search space, reducing the initial bias of the surrogate model.

📖
terms

Trust Region Based Optimization

Approach that restricts the search to a trust region around the current best solution, dynamically adjusting it to accelerate local convergence.

📖
terms

Noisy Objective Function

Evaluation function whose results are affected by random noise, requiring adaptations of the Gaussian process and acquisition functions to handle uncertainty.

📖
terms

Automated Hyperparameter Tuning

Process that uses algorithms such as Bayesian optimization to automatically find the combination of hyperparameters that optimizes the performance of a machine learning model.

🔍

No results found