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Energy Efficiency and Robustness of Advanced Machine Learning Architectures A Cross-Layer Approach - Alberto Marchisio, Muhammad Shafique 2025 PDF | EPUB CRC Press BOOKS
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Energy Efficiency and Robustness of Advanced Machine Learning Architectures A Cross-Layer Approach
Author: Alberto Marchisio, Muhammad Shafique
Year: 2025
Pages: 361
Format: PDF | EPUB
File size: 51.9 MB
Language: ENG



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Book Energy Efficiency and Robustness of Advanced Machine Learning Architectures A CrossLayer Approach The book "Energy Efficiency and Robustness of Advanced Machine Learning Architectures A CrossLayer Approach" is a comprehensive guide to understanding the development and implementation of advanced machine learning architectures that prioritize energy efficiency and robustness. The book explores the intersection of these two critical factors in the context of cross-layer approaches, providing readers with a deep dive into the latest advancements in the field. It covers the principles, techniques, and applications of energy-efficient and robust machine learning architectures, making it an essential resource for researchers, practitioners, and students alike. The book begins by discussing the importance of energy efficiency and robustness in modern machine learning systems, highlighting their significance in various applications such as edge computing, autonomous vehicles, and smart grids. It then delves into the fundamentals of cross-layer approaches, explaining how they can be used to optimize energy consumption while maintaining robust performance.
Book Energy Efficiency and Robustness of Advanced Machine arning Architectures A CrossLayer Approach Книга "Энергоэффективность и надежность расширенных архитектур машинного обучения. Книга исследует пересечение этих двух критических факторов в контексте межуровневых подходов, предоставляя читателям глубокое погружение в последние достижения в этой области. Он охватывает принципы, методы и применения энергоэффективных и надежных архитектур машинного обучения, что делает его важным ресурсом для исследователей, практиков и студентов. Книга начинается с обсуждения важности энергоэффективности и надежности в современных системах машинного обучения, подчеркивая их значение в различных приложениях, таких как периферийные вычисления, автономные транспортные средства и интеллектуальные сети. Затем он углубляется в основы межуровневых подходов, объясняя, как их можно использовать для оптимизации энергопотребления при сохранении высокой производительности.
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