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This paper advances the theory and practice of Domain Generalization (DG) in machine learning.
An overview of statistical learning theory
V. N. Vapnik · 1999
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Detecting change in data streams
D. Kifer, S. Ben-David, and J. Gehrke · 2004
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Analysis of representations for domain adaptation
S. Ben-David, J. Blitzer, K. Crammer, and F. Pereira · 2007
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A theory of learning from different domains
S. Ben-David, J. Blitzer, K. Crammer, A. Kulesza, F. Pereira, and J. W. Vaughan · 2010
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Barycenters in the Wasserstein space
M. Agueh and G. Carlier · 2011
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Generalizing from several related classification tasks to a new unlabeled sample
G. Blanchard, G. Lee, and C. Scott · 2011
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Information theory: coding theorems for discrete memoryless systems
I. Csiszár and J. Körner · 2011
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Sinkhorn distances: Lightspeed computation of optimal transport
M. Cuturi · 2013
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Unbiased metric learning: On the utilization of multiple datasets and web images for softening bias
C. Fang, Y. Xu, and D. N. Rockmore · 2013
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Fast computation of wasserstein barycenters
M. Cuturi and A. Doucet · 2014
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Adam: A method for stochastic optimization
D. P. Kingma and J. Ba · 2015
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Optimal transport for applied mathematicians
F. Santambrogio · 2015
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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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Wasserstein continuity of entropy and outer bounds for interference channels
Y. Polyanskiy and Y. Wu · 2016
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Deep coral: Correlation alignment for deep domain adaptation
B. Sun and K. Saenko · 2016
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Deeper, broader and artier domain generalization
D. Li, Y. Yang, Y.-Z. Song, and T. M. Hospedales · 2017
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Theoretical analysis of domain adaptation with optimal transport
I. Redko, A. Habrard, and M. Sebban · 2017
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Deep hashing network for unsupervised domain adaptation
H. Venkateswara, J. Eusebio, S. Chakraborty, and S. Panchanathan · 2017
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Recognition in terra incognita
S. Beery, G. Van Horn, and P. Perona · 2018
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Domain generalization with adversarial feature learning
H. Li, S. J. Pan, S. Wang, and A. C. Kot · 2018
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Deep domain generalization via conditional invariant adversarial networks
Y. Li, X. Tian, M. Gong, Y. Liu, T. Liu, K. Zhang, and D. Tao · 2018
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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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Domain generalization via entropy regularization
S. Zhao, M. Gong, T. Liu, H. Fu, and D. Tao · 2020
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Domain generalization by marginal transfer learning
G. Blanchard, A. A. Deshmukh, Ü. Dogan, G. Lee, and C. Scott · 2021
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Rethinking domain generalization baselines
F. C. Borlino, A. D’Innocente, and T. Tommasi · 2021
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Swad: Domain generalization by seeking flat minima
J. Cha, S. Chun, K. Lee, H.-C. Cho, S. Park, Y. Lee, and S. Park · 2021
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Scalable computations of Wasserstein barycenter via input convex neural networks
J. Fan, A. Taghvaei, and Y. Chen · 2021
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Pot: Python optimal transport
R. Flamary, N. Courty, A. Gramfort, M. Z. Alaya, A. Boisbunon, S. Chambon, L. Chapel, A. Corenflos, K. Fatras, N. Fournier, L. Gautheron, N. T. Gayraud, H. Janati, A. Rakotomamonjy, I. Redko, A. Rolet, A. Schutz, V. Seguy, D. J. Sutherland, R. Tavenard, A. Tong, and T. Vayer · 2021
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Generalizing to unseen domains via distribution matching
I. Albuquerque, J. Monteiro, M. Darvishi, T. H. Falk, and I. Mitliagkas · 2019
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M. Arjovsky, L. Bottou, I. Gulrajani, and D. Lopez-Paz · 2019
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EEG-based driver drowsiness estimation using feature weighted episodic training
Y. Cui, Y. Xu, and D. Wu · 2019
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Domain generalization via model-agnostic learning of semantic features
Q. Dou, D. Coelho de Castro, K. Kamnitsas, and B. Glocker · 2019
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Interpolating between optimal transport and MMD using sinkhorn divergences
J. Feydy, T. Séjourné, F.-X. Vialard, S.-i. Amari, A. Trouve, and G. Peyré · 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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In search of lost domain generalization
I. Gulrajani and D. Lopez-Paz · 2021
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Out-of-distribution generalization via risk extrapolation (rex)
D. Krueger, E. Caballero, J.-H. Jacobsen, A. Zhang, J. Binas, D. Zhang, R. L. Priol, and A. Courville · 2021
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Domain adaptation for robust workload level alignment between sessions and subjects using fNIRS
B. Lyu, T. Pham, G. Blaney, Z. Haga, A. Sassaroli, S. Fantini, and S. Aeron · 2021
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Reducing domain gap by reducing style bias
H. Nam, H. Lee, J. Park, W. Yoon, and D. Yoo · 2021
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Domain generalization via optimal transport with metric similarity learning
F. Zhou, Z. Jiang, C. Shui, B. Wang, and B. Chaib-draa · 2021
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Wasserstein iterative networks for barycenter estimation
A. Korotin, V. Egiazarian, L. Li, and E. Burnaev · 2022
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Domain generalization using pretrained models without fine-tuning
Z. Li, K. Ren, X. Jiang, B. Li, H. Zhang, and D. Li · 2022
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Trade-off between reconstruction loss and feature alignment for domain generalization
T. Nguyen, B. Lyu, P. Ishwar, M. Scheutz, and S. Aeron · 2022
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Generalizing to unseen domains: A survey on domain generalization
J. Wang, C. Lan, C. Liu, Y. Ouyang, T. Qin, W. Lu, Y. Chen, W. Zeng, and P. Yu · 2022
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Domain generalization: A survey
K. Zhou, Z. Liu, Y. Qiao, T. Xiang, and C. C. Loy · 2023
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