This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks.
Energy Efficiency and Robustness of Advanced Machine Learning Architectures
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$282.00
Description
This book tackles these challenges by exploiting the unique features of advanced ML models and investigates cross-layer concepts and techniques to engage both hardware and software-level methods to build robust and energy-efficient architectures for these advanced ML networks.
Today, machine learning algorithms are often distributed across multiple machines to leverage more computing power and more data. However, the use of a distributed framework entails a variety of...
This book presents a collection of energy production and distribution problems identified by the members of the COST Action TD1207 "Mathematical Optimization in the Decision Support Systems for...
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