DiTMoS: Delving into diverse tiny-model selection on microcontrollers

• Main Authors: MA, Xiao, HE, Shengfeng, QIAO, Hezhe, MA, Dong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: embedded machine learning; model diversity; model selection; adversarial training; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/8670; https://ink.library.smu.edu.sg/context/sis_research/article/9673/viewcontent/2403.09035.pdf
• Institution: Singapore Management University

Enabling efficient and accurate deep neural network (DNN) inference on microcontrollers is non-trivial due to the constrained on-chip resources. Current methodologies primarily focus on compressing larger models yet at the expense of model accuracy. In this paper, we rethink the problem from the inv...