Before revision:  The algorithm achieves O\left(m ^2 n\right) expected regret under the stochastic input model and O\left((m ^2 +\log n)n\right) expected regret under the random permutation model, and it achieves O(m n) expected constraint violation under both models, where n is the number of decision variables and m is the number of constraints.
After revision:  The algorithm achieves O\left(m ^2 n\right) expected regret under the stochastic input model and O\left((m +\log n)n\right) expected regret under the random permutation model, and it achieves O(m n) expected constraint violation under both models, where n is the number of decision variables and m is the number of constraints.