papers

Gong, Boqing, Grauman, Kristen, and Sha, Fei. Connecting the dots with landmarks: Discriminatively learning domain-invariant features for unsupervised domain
adaptation. In ICML, pp. 222–230, 2013.

Baktashmotlagh, Mahsa, Harandi, Mehrtash Tafazzoli,
Lovell, Brian C., and Salzmann, Mathieu. Unsupervised
domain adaptation by domain invariant projection. In
ICCV, pp. 769–776, 2013.

Fernando, Basura, Habrard, Amaury, Sebban, Marc, and
Tuytelaars, Tinne. Unsupervised visual domain adaptation using subspace alignment. In ICCV, 2013.

S. Chopra, S. Balakrishnan and Gopalan, R. Dlid: Deep
learning for domain adaptation by interpolating between
domains. In ICML Workshop on Challenges in Representation Learning, 2013.


Goodfellow, Ian, Pouget-Abadie, Jean, Mirza, Mehdi, Xu,
Bing, Warde-Farley, David, Ozair, Sherjil, Courville,
Aaron, and Bengio, Yoshua. Generative adversarial nets.
In NIPS, 2014.


Tzeng, Eric, Hoffman, Judy, Zhang, Ning, Saenko, Kate,
and Darrell, Trevor. Deep domain confusion: Maximizing for domain invariance. CoRR, abs/1412.3474, 2014