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#multi-armed-bandits News & Analysis

2 articles tagged with #multi-armed-bandits. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

2 articles
AIBullisharXiv โ€“ CS AI ยท Mar 47/104
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Learning Contextual Runtime Monitors for Safe AI-Based Autonomy

Researchers introduce a novel framework for learning context-aware runtime monitors for AI-based control systems in autonomous vehicles. The approach uses contextual multi-armed bandits to select the best controller for current conditions rather than averaging outputs, providing theoretical safety guarantees and improved performance in simulated driving scenarios.

AINeutralarXiv โ€“ CS AI ยท Mar 34/104
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Near-Optimal Regret for KL-Regularized Multi-Armed Bandits

Researchers developed a new analysis of KL-regularized multi-armed bandits (MABs) using KL-UCB algorithm, achieving near-optimal regret bounds. The study provides the first high-probability regret bound with linear dependence on the number of arms and establishes matching lower bounds, offering comprehensive understanding across all regularization regimes.

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