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Found 3 papers, 1 papers with code
Design-based conformal prediction
Conformal prediction is an assumption-lean approach to generating distribution-free prediction intervals or sets, for nearly arbitrary predictive models, with guaranteed finite-sample coverage.
Recall Distortion in Neural Network Pruning and the Undecayed Pruning Algorithm
In this work, we study such relative distortions in recall by hypothesizing an intensification effect that is inherent to the model.
Household poverty classification in data-scarce environments: a machine learning approach
We describe a method to identify poor households in data-scarce countries by leveraging information contained in nationally representative household surveys.
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