Probabilistic inference in machine learning using a quantum oracle
US11030548B1 · kind B1 · utility
2Cited by
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Key dates
| Filing date | May 15, 2019 |
| Grant date | Jun 8, 2021 |
| Priority date | — |
| Expiry date | Oct 10, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N10/60
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods, systems, and apparatus, including computer programs encoded on computer storage media, for using a quantum oracle to make inference in complex machine learning models that is capable of solving artificial intelligent problems. Input to the quantum oracle is derived from the training data and the model parameters, which maps at least part of the interactions of interconnected units of the model to the interactions of qubits in the quantum oracle. The output of the quantum oracle is used to determine values used to compute loss function values or loss function gradient values or both during a training process.
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