380 citations · 393 across the 4 of their papers we have counts for
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cs.LG2019★ 1 cited
Learning Condensed and Aligned Features for Unsupervised Domain Adaptation Using Label Propagation
Jaeyoon Yoo, Changhwa Park, Yongjun Hong +1
Unsupervised domain adaptation aiming to learn a specific task for one domain using another domain data has emerged to address the labeling issue in supervised learning, especially…
cs.LG2017★ 380 cited
How Generative Adversarial Networks and Their Variants Work: An Overview
Yongjun Hong, Uiwon Hwang, Jaeyoon Yoo +1
Generative Adversarial Networks (GAN) have received wide attention in the machine learning field for their potential to learn high-dimensional, complex real data distribution. Spec…