Revealing graph bandits for maximizing local influence
This research proposes BARE, a bandit revelation algorithm for finding the most influential node in a graph sequentially when only local influence information is known at each step. BARE scales its performance based on the 'detectable dimension' rather than the total number of nodes, offering practical solutions for large social networks where full graph knowledge is unavailable.