RL-OSHeDA, a two-stage representation learning method with pseudo-labeling, outperforms existing domain adaptation baselines on 56 open-set heterogeneous domain adaptation tasks.
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Open-Set Heterogeneous Domain Adaptation: Theoretical Analysis and Algorithm
RL-OSHeDA, a two-stage representation learning method with pseudo-labeling, outperforms existing domain adaptation baselines on 56 open-set heterogeneous domain adaptation tasks.