Description

Homogeneous (where the metrics are the same for both source and target) asymmetric transformation mapping transforms the source feature space to align with that of the target or the target to that of the source. This, in effect, bridges the feature space gap and reduces the problem into a homogeneous transfer problem when further distribution differences need to be corrected.

Technical Details

Relationships

Related Techniques

• D3A-IBTL Instance-based Transfer Learning (Unpublished)
• D3A-HBTL Hybrid-based Transfer Learning (Unpublished)
• D3A-SFTL Symmetric Feature-based Transfer Learning (Unpublished)
• D3A-HFBTL Heterogeneous Feature-based Transfer Learning (Unpublished)
• D3A-HTL Heterogeneous Transfer Learning (Unpublished)
• D3A-PBTL Parameter-based Transfer Learning (Unpublished)
• D3A-RBTL Relational-based Transfer Learning (Unpublished)
• D3A-HAFBTL Heterogeneous Asymmetric Feature-based Transfer Learning (Unpublished)