Transfer learning achieves sample complexity O(m^{-(α+1)/d}) for d>3 via optimal transport, outperforming direct learning's O(m^{-p/d}) when target models are not smooth.
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Sample Complexity of Transfer Learning: An Optimal Transport Approach
Transfer learning achieves sample complexity O(m^{-(α+1)/d}) for d>3 via optimal transport, outperforming direct learning's O(m^{-p/d}) when target models are not smooth.