Geodesic flow kernel for unsupervised domain adaptation

@article{Gong2012GeodesicFK,
  title={Geodesic flow kernel for unsupervised domain adaptation},
  author={Boqing Gong and Yuan Shi and Fei Sha and Kristen Grauman},
  journal={2012 IEEE Conference on Computer Vision and Pattern Recognition},
  year={2012},
  pages={2066-2073}
}
In real-world applications of visual recognition, many factors - such as pose, illumination, or image quality - can cause a significant mismatch between the source domain on which classifiers are trained and the target domain to which those classifiers are applied. As such, the classifiers often perform poorly on the target domain. Domain adaptation techniques aim to correct the mismatch. Existing approaches have concentrated on learning feature representations that are invariant across domains… CONTINUE READING
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