Distributionally Robust Learning for Uncertainty Calibration under Domain Shift
@inproceedings{Wang2020DistributionallyRL, title={Distributionally Robust Learning for Uncertainty Calibration under Domain Shift}, author={Haoxu Wang and Anqi Liu and Zhiding Yu and Junchi Yan and Yisong Yue and Anima Anandkumar}, year={2020} }
We propose a framework for learning calibrated uncertainties under domain shifts. We consider the case where the source (training) distribution differs from the target (test) distribution. We detect such domain shifts through the use of binary domain classifier and integrate it with the task network and train them jointly endto-end. The binary domain classifier yields a density ratio that reflects the closeness of a target (test) sample to the source (training) distribution. We employ it to…
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