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公开(公告)号：US10592519B2
公开(公告)日：2020-03-17
申请号：US15084366
申请日：2016-03-29
发明人： Xiaodong He , Li Deng , Jianfeng Gao , Wen-tau Yih , Moontae Lee , Paul Smolensky
IPC分类号： G06F16/2458 , G06F16/2453
摘要： A processing unit can determine multiple representations associated with a statement, e.g., subject or predicate representations. In some examples, the representations can lack representation of semantics of the statement. The computing device can determine a computational model of the statement based at least in part on the representations. The computing device can receive a query, e.g., via a communications interface. The computing device can determine at least one query representation, e.g., a subject, predicate, or entity representation. The computing device can then operate the model using the query representation to provide a model output. The model output can represent a relationship between the query representations and information in the model. The computing device can, e.g., transmit an indication of the model output via the communications interface. The computing device can determine mathematical relationships between subject representations and attribute representations for multiple statements, and determine the model using the relationships.
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公开(公告)号：US20210065037A1
公开(公告)日：2021-03-04
申请号：US16446511
申请日：2019-06-19
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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公开(公告)号：US20170286494A1
公开(公告)日：2017-10-05
申请号：US15084366
申请日：2016-03-29
发明人： Xiaodong He , Li Deng , Jianfeng Gao , Wen-tau Yih , Moontae Lee , Paul Smolensky
IPC分类号： G06F17/30
摘要： A processing unit can determine multiple representations associated with a statement, e.g., subject or predicate representations. In some examples, the representations can lack representation of semantics of the statement. The computing device can determine a computational model of the statement based at least in part on the representations. The computing device can receive a query, e.g., via a communications interface. The computing device can determine at least one query representation, e.g., a subject, predicate, or entity representation. The computing device can then operate the model using the query representation to provide a model output. The model output can represent a relationship between the query representations and information in the model. The computing device can, e.g., transmit an indication of the model output via the communications interface. The computing device can determine mathematical relationships between subject representations and attribute representations for multiple statements, and determine the model using the relationships.
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公开(公告)号：US11783222B2
公开(公告)日：2023-10-10
申请号：US16446511
申请日：2019-06-19
摘要： A method of training a quantum computer employs quantum algorithms. The method comprises loading, into the quantum computer, a description of a quantum Boltzmann machine, and training the quantum Boltzmann machine according to a protocol, wherein a classification error is used as a metric for the protocol.
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