  Complex risk is a critical factor for both intelligent systems and risk
management. In this paper, we consider a special class of risk statistics,
named complex risk statistics. Our result provides a new approach for
addressing complex risk, especially in deep neural networks. By further
developing the properties related to complex risk statistics, we are able to
derive dual representation for such risk.
