The introduction of large-margin based discriminative methods for optimizing statistical machine translation systems in recent years has allowed exploration into many new types of features for the translation process. By removing the limitation on the number of parameters which can be optimized, these methods have allowed integrating millions of sparse features. However, these methods have not ...

Algorithms based on statistical models compete favorably with other global optimization algorithms as shown by extensive testing results. A theoretical inadequacy of previously used statistical models for smooth objective functions was eliminated by the authors who in a recent paper have constructed a P-algorithm for a statistical model of smooth functions. In the present note a modification of...

Nonparametric maximum likelihood (NPML) for mixture models is a technique for estimating mixing distributions, which has a long and rich history in statistics going back to the 1950s (Kiefer and Wolfowitz, 1956; Robbins, 1950). However, NPMLbased methods have been considered to be relatively impractical because of computational and theoretical obstacles. Recent work focusing on approximate NPML...