公开(公告)号：US12061952B2

公开(公告)日：2024-08-13

申请号：US17410553

申请日：2021-08-24

Applicant: International Business Machines Corporation

Inventor： Aaron K. Baughman ,  Gururaja Hebbar ,  Micah Forster ,  Kavitha Hassan Yogaraj ,  Yoshika Chhabra

IPC: G06F40/20 ,  G06F15/16 ,  G06N10/00

CPC classification number: G06N10/00 ,  G06F15/16 ,  G06F40/20

Abstract: Using a model executing on a classical processor, a set of classical features is scored. The scored set of classical features is divided into a set of feature groups, a number of classical features in a group determined according to a qubit capability of a quantum processor. Using a model executing on the quantum processor and a group of the scored set of classical features, a set of quantum features is scored. The score of a quantum feature is adjusted according to an accuracy of the quantum data model. The scored set of classical features and the scored set of quantum features are combined according to a measure of differences between the scored set of classical features and the scored set of quantum features. Using the combined set of scored features and a first set of input data of a resource, a valuation of a resource is calculated.

公开(公告)号：US20240354854A1

公开(公告)日：2024-10-24

申请号：US18298445

申请日：2023-04-11

Applicant: International Business Machines Corporation ,  E.ON Digital Technology GmbH

Inventor： Gabriele Francesco Maria Agliardi ,  Kavitha Hassan Yogaraj ,  Francesco Tacchino ,  Antonio Mezzacapo ,  Gururaja Hebbar ,  Omar Shehab ,  Cortiana Giorgio ,  Corey O'Meara ,  Kumar Jang Bahadur Ghosh ,  Piergiacomo Sabino

IPC: G06Q40/06 ,  G06N10/60

CPC classification number: G06Q40/06 ,  G06N10/60

Abstract: A system can comprise a memory that stores computer executable components, and a processor, operably coupled to the memory, that executes the computer executable components comprising: an evaluating component that employs a quantum register to output a processed vector based on a first variable, of set of variables indexed over a selected dimension, and a valuation component that approximates a value function and that, based on the approximating, outputs a valuation amount representing provision of an aspect over the selected dimension, wherein the value function is a function of an inner product of a set of processing functions that are based on the set of variables, including the first variable, wherein a first processing function of the set of processing functions and of the inner product is based on the processed vector, and wherein the set of variables correspond to conditions defining the provision of the aspect.

公开(公告)号：US20230065684A1

公开(公告)日：2023-03-02

申请号：US17410553

申请日：2021-08-24

Applicant: International Business Machines Corporation

Inventor： Aaron K. Baughman ,  Gururaja Hebbar ,  Micah Forster ,  Kavitha Hassan Yogaraj ,  Yoshika Chhabra

IPC: G06N10/00 ,  G06F40/20 ,  G06F15/16

Abstract: Using a model executing on a classical processor, a set of classical features is scored. The scored set of classical features is divided into a set of feature groups, a number of classical features in a group determined according to a qubit capability of a quantum processor. Using a model executing on the quantum processor and a group of the scored set of classical features, a set of quantum features is scored. The score of a quantum feature is adjusted according to an accuracy of the quantum data model. The scored set of classical features and the scored set of quantum features are combined according to a measure of differences between the scored set of classical features and the scored set of quantum features. Using the combined set of scored features and a first set of input data of a resource, a valuation of a resource is calculated.

公开(公告)号：US20230010615A1

公开(公告)日：2023-01-12

申请号：US17367899

申请日：2021-07-06

Applicant: International Business Machines Corporation

Inventor： Aaron K. Baughman ,  Souvik Mazumder ,  Mohit Trivedi ,  Gururaja Hebbar ,  Daniel Joseph Fry ,  Kavitha Hassan Yogaraj ,  Herman Colquhoun

IPC: G06N5/04 ,  G06N10/00 ,  G06F40/20

Abstract: Using a classical data model executing on a classical processor, a set of classical features is scored. A classical feature comprises a first attribute of a resource, and a score of the classical feature comprises an evaluation of a utility of the classical feature in predicting a result involving the resource. Using a quantum data model executing on a quantum processor and the scored set of classical features, a set of quantum features is scored. The scored set of classical features and the scored set of quantum features are correlated, forming a combined set of scored features. Using the combined set of scored features and a first set of input data of a resource, a valuation of the resource is calculated.