June 5, 2024, 4:44 a.m. | Massimo Pavan, Gioele Mombelli, Francesco Sinacori, Manuel Roveri

cs.LG updates on arXiv.org arxiv.org

arXiv:2406.01655v1 Announce Type: cross
Abstract: TinyML is a novel area of machine learning that gained huge momentum in the last few years thanks to the ability to execute machine learning algorithms on tiny devices (such as Internet-of-Things or embedded systems). Interestingly, research in this area focused on the efficient execution of the inference phase of TinyML models on tiny devices, while very few solutions for on-device learning of TinyML models are available in the literature due to the relevant overhead …

abstract algorithms arxiv cs.lg cs.sd devices eess.as embedded internet machine machine learning machine learning algorithms novel on-device learning research speaker systems tinyml type verification

Senior Data Engineer

@ Displate | Warsaw

Solution Architect

@ Philips | Bothell - B2 - Bothell 22050

Senior Product Development Engineer - Datacenter Products

@ NVIDIA | US, CA, Santa Clara

Systems Engineer - 2nd Shift (Onsite)

@ RTX | PW715: Asheville Site W Asheville Greenfield Site TBD , Asheville, NC, 28803 USA

System Test Engineers (HW & SW)

@ Novanta | Barcelona, Spain

Senior Solutions Architect, Energy

@ NVIDIA | US, TX, Remote