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Domain adaptation is an important problem and often needed for real-world applications.
A database for handwritten text recognition research
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Domain adaptation: Learning bounds and algorithms
Y. Mansour, M. Mohri, and A. Rostamizadeh · 2009
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A theory of learning from different domains
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K. Saenko, B. Kulis, M. Fritz, and T. Darrell · 2010
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A. Khosla, T. Zhou, T. Malisiewicz, A. A. Efros, and A. Torralba · 2012
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D. P. Kingma and M. Welling · 2013
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Domain generalization via invariant feature representation
K. Muandet, D. Balduzzi, and B. Schölkopf · 2013
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Domain-adversarial neural networks
H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, and M. Marchand · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2014
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Domain generalization for object recognition with multi-task autoencoders
M. Ghifary, W. B. Kleijn, M. Zhang, and D. Balduzzi · 2015
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Deep variational information bottleneck
A. A. Alemi, I. Fischer, J. V. Dillon, and K. Murphy · 2016
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Wasserstein distance guided representation learning for domain adaptation
J. Shen, Y. Qu, W. Zhang, and Y. Yu · 2018
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Regularized learning for domain adaptation under label shifts
K. Azizzadenesheli, A. Liu, F. Yang, and A. Anandkumar · 2019
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Support and invertibility in domain-invariant representations
F. D. Johansson, D. Sontag, and R. Ranganath · 2019
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Contrastive adaptation network for unsupervised domain adaptation
G. Kang, L. Jiang, Y. Yang, and A. G. Hauptmann · 2019
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Pytorch: An imperative style, high-performance deep learning library
A. Paszke, S. Gross, F. Massa, A. Lerer, J. Bradbury, G. Chanan, T. Killeen, Z. Lin, N. Gimelshein, L. Antiga, A. Desmaison, A. Kopf, E. Yang, Z. DeVito, M. Raison, A. Tejani, S. Chilamkurthy, B. Steiner, L. Fang, J. Bai, and S. Chintala · 2019
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Domain-adversarial training of neural networks
Y. Ganin, E. Ustinova, H. Ajakan, P. Germain, H. Larochelle, F. Laviolette, M. Marchand, and V. Lempitsky · 2016
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Nips 2016 tutorial: Generative adversarial networks
I. Goodfellow · 2016
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Deep residual learning for image recognition
K. He, X. Zhang, S. Ren, and J. Sun · 2016
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Deep coral: Correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
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On convergence and stability of gans
N. Kodali, J. Abernethy, J. Hays, and Z. Kira · 2017
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Deeper, broader and artier domain generalization
D. Li, Y. Yang, Y.-Z. Song, and T. Hospedales · 2017
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Visda: The visual domain adaptation challenge, 2017
X. Peng, B. Usman, N. Kaushik, J. Hoffman, D. Wang, and K. Saenko · 2017
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d-sne: Domain adaptation using stochastic neighborhood embedding
X. Xu, X. Zhou, R. Venkatesan, G. Swaminathan, and O. Majumder · 2019
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Bridging theory and algorithm for domain adaptation
Y. Zhang, T. Liu, M. Long, and M. Jordan · 2019
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On learning invariant representations for domain adaptation
H. Zhao, R. T. Des Combes, K. Zhang, and G. Gordon · 2019
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Domain adaptation with conditional distribution matching and generalized label shift
R. T. d. Combes, H. Zhao, Y.-X. Wang, and G. Gordon · 2020
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In search of lost domain generalization
I. Gulrajani and D. Lopez-Paz · 2020
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Domain-invariant representation learning for sim-to-real transfer
A. K. Tanwani · 2020
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Deep subdomain adaptation network for image classification
Y. Zhu, F. Zhuang, J. Wang, G. Ke, J. Chen, J. Bian, H. Xiong, and Q. He · 2020
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f-domain-adversarial learning: Theory and algorithms
D. Acuna, G. Zhang, M. T. Law, and S. Fidler · 2021
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Domain invariant representation learning with domain density transformations
A. T. Nguyen, T. Tran, Y. Gal, and A. G. Baydin · 2021
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