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Junyu Liu1,2,3,4,5,6, Minzhao Liu7,8, Jin-Peng Liu9,10,11
1Pritzker School of Molecular Engineering, The University of Chicago, Chicago, IL, 60637, USA.
容错量子计算可能为训练大型机器学习模型提供高效的解决方案. 这种方法显示出降低人工智能计算成本的潜力,特别是在稀疏和消散模型中.
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