Domain adaptation
Domain Adaptation for Statistical Machine Translation with Domain Dictionary and Monolingual Corpora
... in- domain dictionary also helps to improve the translation quality, as "CLDC+BTEC+Dic" achieves an improvement of about 1 BLEU score in comparison with "CLDC+BTEC"; (b) the method ...
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Domain Adaptation with BERT based Domain Classification and Data Selection
... 2011), domain discrep- ancy regularization and domain adversarial train- ing (Shah et ...a domain invariant repre- sentation for neural network ...main adaptation studies have focused on tasks ...
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A General Regularization Framework for Domain Adaptation
... Domain adaptation (DA) is an important problem that has received substantial attention in natural lan- guage processing (Blitzer et ...easy domain adapta- tion (FEDA) in Daum´e III (2007), Finkel and ...
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Biased Representation Learning for Domain Adaptation
... source domain dataset to arbitrary new ...two domain adaptation tasks show that our biased learners identify signif- icantly better sets of features than unbiased learners, resulting in a relative ...
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Domain Adaptation for Relation Extraction with Domain Adversarial Neural Network
... for domain adap- tation is to construct a target-domain- specific labeled dataset for adapting the ...pervised domain adaptation method which only requires labels from the source do- ...a ...
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Domain Adaptation for MT: A Study with Unknown and Out of Domain Tasks
... desired domain for both NMT and ...using domain adaptation methods ...in- domain data such as system interpolation, instance weighting and data ...the domain of user translation ...
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Improving Domain Adaptation Translation with Domain Invariant and Specific Information
... each domain is pre- dicted on the output of both the common decoder and its private ...out-of- domain decoder is used to help train the common encoder and decoder better which can also help in- ...
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Domain Adaptation with Structural Correspondence Learning
... domain adaptation. By using just the unlabeled data from the target domain, however, we can view domain adaptation as a standard semisupervised learning ...source domain to be ...
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Metric Learning for Graph Based Domain Adaptation
... for domain adaptation have recently been proposed (Arnold et ...source domain, while certain amount of unlabeled target data is also used during ...any domain is expensive to ...high ...
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Domain Independent Authorship Attribution without Domain Adaptation
... into domain adaptation for au- thorship attribution, we take a slightly differ- ent push to the problem: we first examine whether there exist domain-independent features that rarely change across ...
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Domain Adaptation via Pseudo In Domain Data Selection
... efficient domain adaptation for the task of statistical machine translation based on extracting sentences from a large general- domain parallel corpus that are most relevant to the target ...small ...
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Sentiment Domain Adaptation with Multiple Sources
... sentiment domain adaptation method based on a deep learning tech- nique, ...the domain label, the domain depen- dence/independence label, and sentiment polari- ...target domain and ...
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Unsupervised Domain Adaptation for Joint Segmentation and POS Tagging
... Modifications can be made to the standard self-training process for domain adaptation to ad- dress the difference in source and target distributions (Margolis, 2011). In Tan et al. (2009), the weights on ...
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Feature-Level Domain Adaptation
... important. Domain shift may be present between digit data sets due to differences in recording ...source domain) that are hardly ever observed in another data set (the target ...target domain, and we ...
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Can Domain Adaptation be Handled as Analogies?
... approached domain adaptation as a search for analogues of the selected features of a reduced BoW used to train a SVM ...new domain without retraining it with a new domain labelled ...new ...
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Consensus Adversarial Domain Adaptation
... Adversarial Domain Adaptation Recently, with the booming development of Generative Adversarial Network (GAN) (Goodfellow et ...the domain shift, which is commonly referred to as adversarial ...
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Instance Weighting for Domain Adaptation in NLP
... the domain adaptation problem arises when the source instances and the target instances are from two different, but related ...the domain adaptation problem from this distributional ...for ...
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Multi Domain Adaptation for SMT Using Multi Task Learning
... with domain information from web por- tal sites 1 , which can be collected to train in-domain ...cal domain adaptation techniques should target more domains rather than just one due to ...
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Domain Adaptation for Authorship Attribution: Improved Structural Correspondence Learning
... first domain adaptation model for authorship attribution to leverage unlabeled ...achieving domain adaptation, and that replacing (in- stead of concatenating) non-pivot features with ...
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Fine grained Knowledge Fusion for Sequence Labeling Domain Adaptation
... news domain, and models trained on these corpora will get sharp declines in per- formance when applied to other domains like so- cial media, forum, literature or patents (Daume III, 2007; Blitzer et ...
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