Pushing the limits of RNN Compression using Kronecker Products Post date July 7, 2021 ← Practical application of tinyML in battery powered anomaly sensors for predictive maintenance of industrial assets → The Deep (Learning) Transformation of Mobile and Embedded Computing
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