Unsupervised Visual Domain Adaptation Using Subspace Alignment

@article{Fernando2013UnsupervisedVD,
  title={Unsupervised Visual Domain Adaptation Using Subspace Alignment},
  author={Basura Fernando and Amaury Habrard and Marc Sebban and Tinne Tuytelaars},
  journal={2013 IEEE International Conference on Computer Vision},
  year={2013},
  pages={2960-2967}
}
In this paper, we introduce a new domain adaptation (DA) algorithm where the source and target domains are represented by subspaces described by eigenvectors. In this context, our method seeks a domain adaptation solution by learning a mapping function which aligns the source subspace with the target one. We show that the solution of the corresponding optimization problem can be obtained in a simple closed form, leading to an extremely fast algorithm. We use a theoretical result to tune the… CONTINUE READING

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