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Machine learning methods can be unreliable when deployed in domains that differ from the domains on which they were trained.
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Rico Sennrich, Barry Haddow and Alexandra Birch · 2015
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Jonas Peters, Peter B\"uhlmann and Nicolai Meinshausen · 2016
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Bharath Hariharan and Ross Girshick · 2017
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Sosuke Kobayashi · 2018
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“Deep domain generalization via conditional invariant adversarial networks”
Ya Li et al · 2018
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Zachary Lipton, Yu-Xiang Wang and Alexander Smola · 2018
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Mingsheng Long, Zhangjie Cao, Jianmin Wang and Michael Jordan · 2018
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Mateo Rojas-Carulla, Bernhard Sch\"olkopf, Richard Turner and Jonas Peters · 2018
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Jun-Hyun Bae, Inchul Choi and Minho Lee · 2021
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Pritish Kamath, Akilesh Tangella, Danica Sutherland and Nathan Srebro · 2021
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Jason Wei and Kai Zou · 2019
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Isabela Albuquerque et al · 2020
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David Krueger et al · 2021
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Evan Liu et al · 2021
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Chaochao Lu, Yuhuai Wu, Jo\’se Hern\’andez-Lobato and Bernhard Sch\"olkopf · 2021
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Alexander Robey, George Pappas and Hamed Hassani · 2021
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Julius Von\"ugelgen et al · 2021
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Yoav Wald, Amir Feder, Daniel Greenfeld and Uri Shalit · 2021
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Olivia Wiles et al · 2021
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Eyal Ben-David, Nadav Oved and Roi Reichart · 2022
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Cian Eastwood et al · 2022
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Yaroslav Ganin et al · 2030
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