Advanced Bandit Algorithms Research

Advanced Bandit Algorithms Research is a research topic within Management Science and Operations Research. Science Explorer counts 8.2k research works in it since 1956. 10.2% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the optimization of multi-armed bandit problems, including topics such as Bayesian optimization, contextual bandits, online learning, convex optimization, Thompson sampling, regret analysis, Gaussian process optimization, hyperparameter optimization, and adversarial multi-armed bandits.

• Bandit Optimization
• Bayesian Optimization
• Contextual Bandits
• Online Learning
• Convex Optimization
• Thompson Sampling
• Regret Analysis
• Gaussian Process Optimization
• Hyperparameter Optimization
• Adversarial Multi-Armed Bandits