We study the contextual bandit problem with linear payoff function. In the traditional contextual bandit problem, the algorithm iteratively chooses an action based on the observed context, and immediately receives a reward for the chosen action. Motivated by a practical need in many applications, we study the design of algorithms under the piled-reward setting, where the rewards are received as...