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Some papers on heterogeneous domain adaptation mention this word, but no good explanation is given. Does anyone understand the meaning of this word.
Paper: Unsupervised Heterogeneous Domain Adaptation with Sparse Feature Transformation
context:
Some semi-supervised HDA methods even utilize parallel unlabeled instances to learn cross-domain representations
A few unsupervised HDA approaches overcome this dependence limitation on labeled target data by learning a common latent correlation subspace based only on parallel instances
he method uses a linear function to transform the source domain features into the target domain features to match the parallel instances, while minimizing the cross domain distribution divergence by aligning the transformed source domain covariance matrix with the target domain covariance matrix.
The text was updated successfully, but these errors were encountered:
Some papers on heterogeneous domain adaptation mention this word, but no good explanation is given. Does anyone understand the meaning of this word.
Paper: Unsupervised Heterogeneous Domain Adaptation with Sparse Feature Transformation
context:
The text was updated successfully, but these errors were encountered: