- 专利标题: QUANTUM ALGORITHMS FOR SUPERVISED TRAINING OF QUANTUM BOLTZMANN MACHINES
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申请号: US16446511申请日: 2019-06-19
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公开(公告)号: US20210065037A1公开(公告)日: 2021-03-04
- 发明人: Nathan O. Wiebe , Alexei Bocharov , Paul Smolensky , Matthias Troyer , Krysta Svore
- 申请人: Microsoft Technology Licensing, LLC
- 申请人地址: US WA Redmond
- 专利权人: Microsoft Technology Licensing, LLC
- 当前专利权人: Microsoft Technology Licensing, LLC
- 当前专利权人地址: US WA Redmond
- 主分类号: G06N20/00
- IPC分类号: G06N20/00 ; G06N10/00
摘要:
Embodiments of a new approach for training a class of quantum neural networks called quantum Boltzmann machines are disclosed. in particular examples, methods for supervised training of a quantum Boltzmann machine are disclosed using an ensemble of quantum states that the Boltzmann machine is trained to replicate. Unlike existing approaches to Boltzmann training, example embodiments as disclosed herein allow for supervised training even in cases where only quantum examples are known (and not probabilities from quantum measurements of a set of states). Further, this approach does not require the use of approximations such as the Golden-Thompson inequality.
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