Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems
Zhe Chen, Yuyan Wang, Dong Liang Lin, Derek Zhiyuan Cheng, Lichan Hong, Ed H., Claire Murong Cui · 2021
Despite deep neural network (DNN)'s impressive prediction performance in various domains, it is well known now that a set of DNN models trained with the same model specification and the exact same training data could produce very different prediction results. People have relied on the state-of-the-art ensemble method to estimate prediction uncertainty. However, ensembles are expensive to train and serve for web-scale traffic systems.