MLCube® is a project that reduces friction for machine learning by ensuring that models are easily portable and reproducible.
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Sep 13, 2024 - Python
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mlcommons
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This repository contains the spreadsheet of the quantitative analysis performed for the paper "Suitability of Forward-Forward and PEPITA Learning to MLCommons-Tiny benchmarks".
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Sep 11, 2023
As described in "Towards Full On-Tiny-Device Learning: Guided Search for a Randomly Initialized Neural Network"
random-forest
resnet
gaussian-processes
bayesian-optimization
extreme-learning-machine
on-device-ml
tinyml
mlcommons
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Updated
Jan 15, 2024 - Python
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