An ensemble of epoch-wise empirical Bayes for few-shot learning

• Main Authors: LIU, Yaoyao, SCHIELE, Bernt, SUN, Qianru
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Confidence predictions; Empirical Bayes; Empirical Bayes models; Hyperparameters; Model performance; Predictive models; Robust predictions; Training epochs; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5594; https://ink.library.smu.edu.sg/context/sis_research/article/6597/viewcontent/1904.08479.pdf
• Institution: Singapore Management University

Few-shot learning aims to train efficient predictive models with a few examples. The lack of training data leads to poor models that perform high-variance or low-confidence predictions. In this paper, we propose to meta-learn the ensemble of epoch-wise empirical Bayes models (E3BM) to achieve robust...