Most Correlated Arms Identification
arXiv:1404.5903v16 citations
Originality Incremental advance
AI Analysis
This addresses a specific problem in multi-armed bandit or correlation analysis, likely incremental as it builds on existing sampling methods.
The paper tackled the problem of identifying the most mutually correlated arms among many arms, showing that adaptive sampling strategies outperform non-adaptive uniform sampling with improved results across various instances.
We study the problem of finding the most mutually correlated arms among many arms. We show that adaptive arms sampling strategies can have significant advantages over the non-adaptive uniform sampling strategy. Our proposed algorithms rely on a novel correlation estimator. The use of this accurate estimator allows us to get improved results for a wide range of problem instances.