Heterogeneous Asymmetric Feature-based Transfer Learning

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.

References

Wang, Q., Mao, K. Z., Wang, B., & Guan, J. (2017). Big data clustering by hybrid optimization algorithm. Journal of Big Data, 4(1), 25. Link.