Description

Homogeneous symmetric transformation takes both the source feature space Xs and target feature space Xt and learns feature transformations as to project each onto a common subspace Xc for adaptation purposes. This derived subspace becomes a domain-invariant feature subspace to associate cross-domain data, and in effect, reduces marginal distribution differences.

Technical Details

Relationships

Related Techniques

• D3A-IBTL Instance-based Transfer Learning (Unpublished)
• D3A-HBTL Hybrid-based Transfer Learning (Unpublished)
• D3A-HFBTL Heterogeneous Feature-based Transfer Learning (Unpublished)
• D3A-HTL Heterogeneous Transfer Learning (Unpublished)
• D3A-PBTL Parameter-based Transfer Learning (Unpublished)
• D3A-RBTL Relational-based Transfer Learning (Unpublished)
• D3A-AFTL Asymmetric Feature-based Transfer Learning (Unpublished)
• D3A-HAFBTL Heterogeneous Asymmetric Feature-based Transfer Learning (Unpublished)