DRASO: Declaratively Regularized Alternating Structural Optimization
Partha Talukdar, Ted Sandler, Mark H. Dredze, Koby Crammer, John C. Blitzer, Fernando M. B. Pereira · 2008
Recent work has shown that Alternating Structural Optimization (ASO) can improve supervised learners by learning feature representations from unlabeled data. However, there is no natural way to include prior knowledge about features into this framework. In this paper, we present Declaratively Regularized Alternating Structural Optimization (DRASO), a principled way for injecting prior knowledge into the ASO framework. We also provide some analysis of the representations learned by our method. 1.