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Domain adaptation addresses the common problem when the target distribution generating our test data drifts from the source (training) distribution.
Sample selection bias as a specification error (with an application to the estimation of labor supply functions), 1977
Heckman, J. J · 1977
Earlier work this paper cites.
Improving predictive inference under covariate shift by weighting the log-likelihood function
Shimodaira, H · 2000
Earlier work this paper cites.
Adjusting the outputs of a classifier to new a priori probabilities: a simple procedure
Saerens, M., Latinne, P., and Decaestecker, C · 2002
Earlier work this paper cites.
Analysis of representations for domain adaptation
Ben-David, S., Blitzer, J., Crammer, K., and Pereira, F · 2007
Earlier work this paper cites.
Correcting sample selection bias by unlabeled data
Huang, J., Gretton, A., Borgwardt, K. M., Schölkopf, B., and Smola, A. J · 2007
Earlier work this paper cites.
Covariate shift by kernel mean matching
Gretton, A., Smola, A. J., Huang, J., Schmittfull, M., Borgwardt, K. M., and Schölkopf, B · 2009
Earlier work this paper cites.
Domain adaptation: Learning bounds and algorithms
Mansour, Y., Mohri, M., and Rostamizadeh, A · 2009
Earlier work this paper cites.
Domain adaptation in regression
Cortes, C. and Mohri, M · 2011
Earlier work this paper cites.
Analysis of kernel mean matching under covariate shift
Yu, Y. and Szepesvári, C · 2012
Cited alongside, same era.
Domain adaptation under target and conditional shift
Zhang, K., Schölkopf, B., Muandet, K., and Wang, Z · 2013
Cited alongside, same era.
Domain adaptation–can quantity compensate for quality?
Ben-David, S. and Urner, R · 2014
Cited alongside, same era.
Generative adversarial nets
Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., and Bengio, Y · 2014
Cited alongside, same era.
Deep domain confusion: Maximizing for domain invariance
Tzeng, E., Hoffman, J., Zhang, N., Saenko, K., and Darrell, T · 2014
Cited alongside, same era.
f-gan: Training generative neural samplers using variational divergence minimization
Nowozin, S., Cseke, B., and Tomioka, R · 2016
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Arjovsky, M., Chintala, S., and Bottou, L · 2017
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Improved training of wasserstein gans
Gulrajani, I., Ahmed, F., Arjovsky, M., Dumoulin, V., and Courville, A. C · 2017
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Cycada: Cycle-consistent adversarial domain adaptation
Hoffman, J., Tzeng, E., Park, T., Zhu, J.-Y., Isola, P., Saenko, K., Efros, A. A., and Darrell, T · 2017
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Detecting and correcting for label shift with black box predictors
Lipton, Z. C., Wang, Y.-X., and Smola, A · 2018
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Domain separation networks
Bousmalis, K., Trigeorgis, G., Silberman, N., Krishnan, D., and Erhan, D · 2016
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Domain-adversarial training of neural networks
Ganin, Y., Ustinova, E., Ajakan, H., Germain, P., Larochelle, H., Laviolette, F., Marchand, M., and Lempitsky, V · 2016
Cited alongside, same era.
A theory of learning from different domains
Ben-David, S., Blitzer, J., Crammer, K., Kulesza, A., Pereira, F., and Vaughan, J. W
Cited in the paper.
Impossibility theorems for domain adaptation
Ben-David, S., Lu, T., Luu, T., and Pál, D
Cited in the paper.
Partial transfer learning with selective adversarial networks
Cao, Z., Long, M., Wang, J., and Jordan, M. I
Cited in the paper.
Partial adversarial domain adaptation
Cao, Z., Ma, L., Long, M., and Wang, J
Cited in the paper.
Adversarial discriminative domain adaptation
Tzeng, E., Hoffman, J., Saenko, K., and Darrell, T
Cited in the paper.
Wasserstein distance guided representation learning for domain adaptation
Shen, J., Qu, Y., Zhang, W., and Yu, Y · 2018
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A dirt-t approach to unsupervised domain adaptation
Shu, R., Bui, H. H., Narui, H., and Ermon, S · 2018
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