Efficient and Robust Algorithms for Adversarial Linear Contextual Bandits

We consider an adversarial variant of the classic K-armed linear contextual bandit problem where the sequence of loss functions associated with each arm are allowed to change without restriction over time. Under the assumption that the d-dimensional contexts are generated i.i.d.~at random from a known distributions, we develop computationally efficient... Show more