Hardware-Aware Probabilistic Machine Learning Models: Learning, Inference and Use Cases

by Laura Isabel Galindez Olascoaga, Wannes Meert, Marian Verhelst

Book Overview

This book proposes probabilistic machine learning models that represent the hardware properties of the device hosting them. These models can be used to evaluate the impact that a specific device configuration may have on resource consumption and performance of the machine learning task, with the overarching goal of balancing the two optimally.

The book first motivates extreme-edge computing in the context of the Internet of Things (IoT)...

• Format: Paperback
• Language: English
• ISBN: 3030740447
• ISBN13: 9783030740443
• Release Date: May 2022
• Publisher: Springer
• Length: 163 Pages
• Weight: 0.56 lbs.
• Dimensions: 0.4" x 6.1" x 9.2"