Search Results for author: Alessandro Montanari

Found 2 papers, 0 papers with code

SensiX++: Bringing MLOPs and Multi-tenant Model Serving to Sensory Edge Devices

no code implementations8 Sep 2021 Chulhong Min, Akhil Mathur, Utku Gunay Acer, Alessandro Montanari, Fahim Kawsar

We present SensiX++ - a multi-tenant runtime for adaptive model execution with integrated MLOps on edge devices, e. g., a camera, a microphone, or IoT sensors.

SensiX: A Platform for Collaborative Machine Learning on the Edge

no code implementations4 Dec 2020 Chulhong Min, Akhil Mathur, Alessandro Montanari, Utku Gunay Acer, Fahim Kawsar

The emergence of multiple sensory devices on or near a human body is uncovering new dynamics of extreme edge computing.

BIG-bench Machine Learning Edge-computing

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