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Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression
In many situations however, the labelling process is able to estimate the variance of such distribution for each label, which can be used as an additional information to mitigate this impact.
Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression using Privileged Information
In this work, we consider this setting and additionally assume that the label generating process is able to provide us with a quantity for the role of each label in the misalignment between the datasets, which we consider to be privileged information.
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