C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction
Sets
C-Adapter: Adapting Deep Classifiers for Efficient Conformal Prediction
Sets
Conformal prediction, as an emerging uncertainty quantification technique, typically functions as post-hoc processing for the outputs of trained classifiers. To optimize the classifier for maximum predictive efficiency, Conformal Training rectifies the training objective with a regularization that minimizes the average prediction set size at a specific error rate. However, the …