Domain Adaptation With Adversarial Training And Graph Embeddings

We propose a novel model that performs adversarial learning based domain adaptation to deal with distribution drifts and graph based semi supervised learning to leverage unlabeled data within a single unified deep learning framework. However obtaining labeled data is a big challenge in many real world problems. Please be patient we are slowly uploading code and preparing readme file.

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