Many of these methods, though, were originally developed with in-domain performance in mind, so their effectiveness in a domain adaptation setting remains unexplored.
we re-evaluate three traditional bootstrapping methods, self-training (Yarowsky, 1995), tri-training (Zhou and Li, 2005), and tritraining with disagreement (Søgaard, 2010) for neural network-based approaches on two NLP tasks with different characteristics, namely, a sequence prediction and a classification task (POS tagging and sentiment analysis).