Efficient meta learning via minibatch proximal update

• Main Authors: ZHOU, Pan, YUAN, Xiao-Tong, XU, Huan, YAN, Shuicheng, FENG, Jiashi
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/8995; https://ink.library.smu.edu.sg/context/sis_research/article/9998/viewcontent/2019_NeurIPS_efficient_meta_learning.pdf
• Institution: Singapore Management University

We address the problem of meta-learning which learns a prior over hypothesis from a sample of meta-training tasks for fast adaptation on meta-testing tasks. A particularly simple yet successful paradigm for this research is model-agnostic meta-learning (MAML). Implementation and analysis of MAML, ho...