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Low-Rank Gradient Approximation For Memory-Efficient On-Device Training Of Deep Neural Network
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Low-Rank Gradient Approximation For Memory-Efficient On-Device Training Of Deep Neural Network
Training machine learning models on mobile devices has the potential of improving both privacy and accuracy of the models. However, one of the major obstacles to achieving this goal is the memory limitation of mobile devices. Reducing training memory enab
Training machine learning models on mobile devices has the potential of improving both privacy and accuracy of the models. However, one of the major obstacles to achieving this goal is the memory limitation of mobile devices. Reducing training memory enab
