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Coping with Label Shift via Distributionally Robust Optimisation
The label shift problem refers to the supervised learning setting where ...
10/23/2020 ∙ by Jingzhao Zhang, et al. ∙
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Robust Large-Margin Learning in Hyperbolic Space
Recently, there has been a surge of interest in representation learning ...
04/11/2020 ∙ by Melanie Weber, et al. ∙
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Making Deep Neural Networks Robust to Label Noise: a Loss Correction Approach
We present a theoretically grounded approach to train deep neural networ...
09/13/2016 ∙ by Giorgio Patrini, et al. ∙
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Predicting accurate probabilities with a ranking loss
In many real-world applications of machine learning classifiers, it is e...
06/18/2012 ∙ by Aditya Menon, et al. ∙
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