Search Results for author: Amr M. Alexandari

Found 2 papers, 1 papers with code

Adapting to Label Shift with Bias-Corrected Calibration

no code implementations25 Sep 2019 Avanti Shrikumar, Amr M. Alexandari, Anshul Kundaje

Label shift refers to the phenomenon where the marginal probability p(y) of observing a particular class changes between the training and test distributions, while the conditional probability p(x|y) stays fixed.

Diabetic Retinopathy Detection Domain Adaptation +2

A General Framework for Abstention Under Label Shift

1 code implementation20 Feb 2018 Amr M. Alexandari, Anshul Kundaje, Avanti Shrikumar

In this work, we present a general framework for abstention that can be applied to optimize any metric of interest, that is adaptable to label shift at test time, and that works out-of-the-box with any classifier that can be calibrated.

Domain Adaptation General Classification +2

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