公开(公告)号：US20240144038A1

公开(公告)日：2024-05-02

申请号：US17978015

申请日：2022-10-31

Applicant: Intuit Inc.

Inventor： Omer ZALMANSON ,  Aviv BEN ARIE

IPC: G06N5/02 ,  G06N5/04

CPC classification number: G06N5/022 ,  G06N5/04

Abstract: A method finds short counterfactuals. The method includes receiving an input vector with a plurality of input features. The method further includes processing, with a model, the input vector to generate a score. The score of the input vector is not to a selected class. The method further includes searching for a counterfactual vector using a cost value and a heuristic value. The searching includes replacing one or more input features of the input vector with one or more counterfactual features to generate the counterfactual vector. The counterfactual vector corresponds to a counterfactual score to the selected class. The method further includes presenting one or more recommendations using the counterfactual vector.

公开(公告)号：US20240256984A1

公开(公告)日：2024-08-01

申请号：US18102075

申请日：2023-01-26

Applicant: Intuit Inc.

Inventor： Aviv BEN ARIE ,  Omer ZALMANSON

IPC: G06N20/20

CPC classification number: G06N20/20

Abstract: A method implements efficient real time serving of ensemble models. The method includes receiving an input and processing the input with an abridged model to generate a set of component scores and an abridged score. The method further includes processing the set of component scores with a deviation threshold to select one of the abridged score and an ensemble score as an output and presenting the output.

公开(公告)号：US20250021844A1

公开(公告)日：2025-01-16

申请号：US18222353

申请日：2023-07-14

Applicant: Intuit, Inc.

Inventor： Omer ZALMANSON ,  Yair HORESH ,  Lior TABORI

IPC: G06N5/046 ,  G06N5/022

Abstract: Certain aspects of the disclosure provide a method for training a machine learning model to predict text containing sensitive information. The method includes extracting one or more features from a historical data set. The method further includes anonymizing the historical data set, including determining, for each feature of the extracted one or more features, tokens containing personally identifiable information (sensitive information); assigning a category placeholder to each of the tokens containing sensitive information; and generating a new data set where each token containing sensitive information is replaced with the assigned category placeholder. The method further includes determining a probability associated with each token containing sensitive information; and training a generalized model to predict anonymized text given the one or more features.

公开(公告)号：US20240005084A1

公开(公告)日：2024-01-04

申请号：US17809658

申请日：2022-06-29

Applicant: INTUIT INC.

Inventor： Omer ZALMANSON ,  Yair HORESH

IPC: G06F40/166 ,  G06N5/04 ,  G06N5/02

CPC classification number: G06F40/166 ,  G06N5/04 ,  G06N5/022

Abstract: Aspects of the present disclosure relate to electronic document creation assistance. Embodiments include determining a current time related to creation of a document by a user and providing inputs to a machine learning model based on the current time. Embodiments include receiving output from the machine learning model based on the inputs and selecting, based on the output, a first recommended item from a plurality of items for inclusion in the document. Embodiments include determining a likelihood of each additional item of the plurality of items co-occurring with the first recommended item based on historical item co-occurrence data. Embodiments include selecting, based on the output and the likelihood of each additional item of the plurality of items co-occurring with the first recommended item, a second recommended item for inclusion in the document and providing, via a user interface, the first recommended item and the second recommended item to the user.