We consider gaussian sequence regression with a convexity constraint on the true sequence. The performance of the MLE is analyzed. We show that the MLE converges at the rate n^{-4/5} in the worst case. Surprisingly, it converges at much faster rates when the true sequence is sparse in a certain sense. Adaptation, in this sense, is therefore achieved by the MLE without any explicit regularization....