Microsoft Technology Licensing, LLC

Paul Smolensky

Li Deng

Jianfeng Gao

Krysta Marie Svore

Xiaodong He

Alexei V Bocharov

Nathan O Wiebe

Matthias Troyer

Wen-tau Yih

Moontae Lee

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.

Quantum algorithms for supervised training of quantum boltzmann machines

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.

Computational-model operation using multiple subject representations

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Paul Smolensky