MPG.eBooks - Table of Contents: Hardware-Aware Probabilistic Machine Learning Models

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

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 ove...

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Bibliographic Details
Main Authors:	Galindez Olascoaga, Laura Isabel, Meert, Wannes (Author), Verhelst, Marian (Author)
Format:	eBook
Language:	English
Published:	Cham Springer International Publishing 2021, 2021
Edition:	1st ed. 2021
Subjects:	Internet Of Things Electronic Circuits Cyber-physical Systems Electronic Circuits And Systems Cooperating Objects (computer Systems)
Online Access:	https://doi.org/10.1007/978-3-030-74042-9?nosfx=y
Collection:	Springer eBooks 2005- - Collection details see MPG.ReNa

Table of Contents:

Introduction
Background
Hardware-Aware Cost Models
Hardware-Aware Bayesian Networks for Sensor Front-End Quality Scaling
Hardware-Aware Probabilistic Circuits
Run-Time Strategies
Conclusions

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

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