We consider a partial-feedback variant of the well-studied online PCA problem where a learner attempts to predict a sequence of d-dimensional vectors in terms of a quadratic loss, while only having limited feedback about the environment's choices. We focus on a natural notion of bandit feedback where the learner only... Show more