Interventional few-shot learning

• Main Authors: YUE, Zhongqi, ZHANG Hanwang, SUN, Qianru, HUA, Xian-Sheng
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Causal intervention; Causal model; Cross-domain; Fine tuning; Interventional; Metalearning; Sample features; State of the art; Artificial Intelligence and Robotics; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5596; https://ink.library.smu.edu.sg/context/sis_research/article/6599/viewcontent/NeurIPS_2020_interventional_few_shot_learning_Paper.pdf
• Institution: Singapore Management University

We uncover an ever-overlooked deficiency in the prevailing Few-Shot Learning (FSL) methods: the pre-trained knowledge is indeed a confounder that limits the performance. This finding is rooted from our causal assumption: a Structural Causal Model (SCM) for the causalities among the pre-trained knowl...