Before revision:  In this paper, we study the effectiveness of JL transform for solving the high dimensional optimization problems with  outliers.
After revision:  In this paper, we consider robust optimization problems in high dimensions. Because a real-world dataset may contain significant noise or even specially crafted samples from some attacker, we are particularly interested in the optimization problems with outliers.