Reviews: Semi-Supervised Learning with Declaratively Specified Entropy Constraints

This paper proposes a method to combine (or ensemble) several SSL heuristics (regularizers) by using a Bayesian optimization approach. The basic idea of the proposed method borrowed from the previous method called D-Learner, which is declared in this paper. Therefore, the proposed method is basically a modification or extension of D-Learner, which seems not to be totally novel. In this perspective, this paper is rather incremental than innovative. The experimental results look fairly well comparing with the methods in previous studies including the baseline D-Learner on the tasks of text classification and relation extraction examined in this paper.