Grzegorz Choczyński

Rethinking Calibration for Early-Exit Neural Networks

Early-exit neural networks~(EENNs) accelerate inference by allowing intermediate classifiers to stop computation once predictions are confident enough. Most methods rely on confidence thresholds for exiting, and consequently, classifier calibration is widely assumed to improve performance. In this w…