These challenges have prompted some researchers to move away from MERT, in favor of linearly decomposable approximations of the evaluation metric (Chiang et al., 2009;Hopkins and May, 2011;Cherry and Foster, 2012), which correspond to easier optimization problems and which naturally incorporate regularization.
recent work (Chiang et al., 2009) has shown that adding thousands or tens of thousands of features can improve MT quality when weights are optimized using a margin-based approximation.