Mar 10, 2020 · In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful ...
In this paper, we discuss the challenges and opportunities associated with the development of a TinyML hardware benchmark. Our short paper is a call to action ...
Mar 13, 2020 · In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful ...
[PDF] Benchmarking TinyML Systems: Challenges and Direction
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The current landscape of TinyML is presented and the challenges and direction towards developing a fair and useful hardware benchmark for TinyML workloads ...
Benchmarking TinyML Systems: Challenges and Direction. Citation: C. R. Banbury, et al., “Benchmarking TinyML Systems: Challenges and Direction”. 2020 ...
Advancements in ultra-low-power tiny machine learning (TinyML) systems promise to unlock an entirely new class of smart applications. However, continued ...
Democratizing machine learning through an open community approach. MLCommons is a community driven research effort.
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C. R. Banbury, et al., “Benchmarking TinyML Systems: Challenges and Direction”. 2020. Filter Pubs By Research Area. Artificial Intelligence (1) · Cloud (8) ...
Benchmarking tinyml systems: Challenges and direction. CR Banbury, VJ Reddi ... Tiny robot learning: Challenges and directions for machine learning in resource- ...
In this position paper, we present the current landscape of TinyML and discuss the challenges and direction towards developing a fair and useful hardware ...