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Simultaneous Semantic Alignment Network for Heterogeneous Domain Adaptation
[article]
2020
arXiv
pre-print
Heterogeneous domain adaptation (HDA) transfers knowledge across source and target domains that present heterogeneities e.g., distinct domain distributions and difference in feature type or dimension. Most previous HDA methods tackle this problem through learning a domain-invariant feature subspace to reduce the discrepancy between domains. However, the intrinsic semantic properties contained in data are under-explored in such alignment strategy, which is also indispensable to achieve promising
arXiv:2008.01677v2
fatcat:my3hq5hbmnhqjkeoyo7p3dlh24