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DLBC: A Deep Learning-Based Consensus in Blockchains for Deep Learning Services
[article]
2020
arXiv
pre-print
With the increasing artificial intelligence application, deep neural network (DNN) has become an emerging task. However, to train a good deep learning model will suffer from enormous computation cost and energy consumption. Recently, blockchain has been widely used, and during its operation, a huge amount of computation resources are wasted for the Proof of Work (PoW) consensus. In this paper, we propose DLBC to exploit the computation power of miners for deep learning training as proof of
arXiv:1904.07349v2
fatcat:njbbs6plpzaapp3oe22p6ajgke