On Statistical Estimation of Edge-Reinforced Random Walks
Researchers have developed a new statistical method for estimating initial edge weights in edge-reinforced random walks (ERRWs). This approach leverages the connection between ERRWs and random walks in a random environment, utilizing a generalized method of moments estimator. The study analyzes the estimator's sample complexity by examining the hyperbolic Gaussian structure of the random environment to bound fluctuations in random edge conductances. AI
IMPACT Introduces a novel statistical estimation technique for reinforced random walks, potentially improving network representation learning and behavioral modeling.