<ul><li>Partial domain adaptation (PDA) problem involves aligning cross-domain samples while distinguishing outlier classes for accurate knowledge transfer.</li><li>Proposed approach, Bi-level Unbalanced Optimal Transport (BUOT), aims to address biases in the widely used weighting framework by incorporating sample-wise and class-wise relations in a unified transport framework.</li><li>BUOT model introduces a cooperation mechanism between sample-level and class-level transport for effective knowledge transfer and outlier identification.</li><li>Experiments on benchmark datasets confirm the competitiveness and efficiency of the BUOT model in tackling the challenges of partial domain adaptation.</li></ul>

Bi-level Unbalanced Optimal Transport for Partial Domain Adaptation

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