Year: 2021
Type: preprint
Abstract: TinyML has rose to popularity in an era where data is everywhere. However, the data that is in most demand is subject to strict privacy and security guarantees. In addition, the deployment of TinyML hardware in the real world has significant memory and communication constraints that traditional ML fails to address. In light of these challenges, we present TinyFedTL, the first implementation of federated transfer learning on a resource-constrained microcontroller.
Source: arXiv (Cornell University)
Authors: Kopparapu, Kavya, Lin, Eric
Institution: Harvard University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3203576251