156 citations · 301 across the 25 of their papers we have counts for
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cs.CV2018★ 44 cited
Unsupervised Domain Adaptation using Regularized Hyper-graph Matching
Debasmit Das, C. S. George Lee
Domain adaptation (DA) addresses the real-world image classification problem of discrepancy between training (source) and testing (target) data distributions. We propose an unsuper…
cs.LG2018★ 64 cited
Sample-to-Sample Correspondence for Unsupervised Domain Adaptation
Debasmit Das, C. S. George Lee
The assumption that training and testing samples are generated from the same distribution does not always hold for real-world machine-learning applications. The procedure of tackli…