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Machine Learning-centric, Energy-Optimized Wireless Systems - Spring 2021 Research Seminar

Paul G. Allen School via YouTube

Overview

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Explore cutting-edge approaches to energy-optimized, machine learning-centric artificial intelligence of things (AIoT) systems in this research seminar. Delve into the challenges of optimized system integration for AIoT devices with strict energy, power, cost, and size constraints. Learn about cross-layer optimization techniques that span deep learning algorithms, wireless communication, digital signal processing, and VLSI hardware architecture. Discover novel hardware-friendly algorithms and VLSI systems designed for ultra-low power and energy-aware wireless IoT applications. Gain insights from Hun-Seok Kim, an assistant professor at the University of Michigan, Ann Arbor, as he shares his expertise in system analysis, algorithm development, and efficient VLSI architectures for various technological domains.

Syllabus

Machine Learning-centric, Energy-Optimized Wireless Systems (Hun-Seok Kim, U of Michigan, Ann Arbor)

Taught by

Paul G. Allen School

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