Equivariance and invariance inductive bias for learning from insufficient data

• Main Authors: WANG, Tan, SUN, Qianru, PRANATA, Sugiri, JAYASHREE, Karlekar, ZHANG, Hanwang
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Inductive Bias; Equivariance; Invariant Risk Minimization; Databases and Information Systems; Graphics and Human Computer Interfaces; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/7513; https://ink.library.smu.edu.sg/context/sis_research/article/8516/viewcontent/ECCV2022_Vipriors_WangTan.pdf
• Institution: Singapore Management University

We are interested in learning robust models from insufficient data, without the need for any externally pre-trained model checkpoints. First, compared to sufficient data, we show why insufficient data renders the model more easily biased to the limited training environments that are usually differen...