Junhao Lin

On the price of exact truthfulness in incentive-compatible online learning with bandit feedback: a regret lower bound for WSU-UX

In one view of the classical game of prediction with expert advice with binary outcomes, in each round, each expert maintains an adversarially chosen belief and honestly reports this belief. We consider a recently introduced, strategic variant of this problem with selfish (reputation-seeking) expert…