… a novel concept of unsupervised progressive domain adaptation based on a deep-… domain
adaptation with multiple datasets that cover multiple domains for effective domain adaptation…

… social network platforms: OAG, Digg, Twitter, and Weibo. We take each social network platform
as a domain. … user performs a social action or not, but the deinition of a social action difers …

… for social group alignment across social networks. In GroupAligner, we propose the cycle
domain adaptation … to align the feature space of social networks in the distribution level, and we …

… , medical assistance) on these social networks. Humanitarian organizations believe timely
access to this important information from social networks can help significantly and reduce …

… • Reduced the gap between social network images and ImageNet by … Domain Adaptation
of our Visual Feature Extractor. As mentioned above, the training data for Domain Adaptation …

… , our SFDA outperforms conventional domain adaptation methods on benchmark datasets. …
in unsupervised domain adaptation. Based on our privacy-preserving domain adaptation, …

… very rapidly these days because of the availability of various social network systems. In the
past decade, the popularity of Social Media (SM) platforms and access to mobile devices and …

… adjust a single step by domain adaptation mechanism, so it is … ) which uses a dual domain
adaptation mechanism to solve … effect of domain adaptation approach for UIL in multi-network …

… domain adaptation scenario. We propose a neural network framework that supports domain
adaptation for … better generalize for domain adaptation. We apply the proposed framework to …

… domain adaptation, instead we use the observed distributions of words on the target side.
Our domain adaptation is motivated by the observation that word frequencies in counties may …