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    Graph data structure for using inter-feature dependencies in machine-learning
    2.
    发明授权
    Graph data structure for using inter-feature dependencies in machine-learning 有权

    公开(公告)号：US11861464B2

    公开(公告)日：2024-01-02

    申请号：US16670543

    申请日：2019-10-31

    Applicant: Adobe Inc.

    Inventor： Ritwik Sinha ,  Sunny Dhamnani

    IPC: G06N20/00 ,  G06F30/20 ,  G06F18/21 ,  G06N7/01 ,  G06F18/2113

    CPC classification number: G06N20/00 ,  G06F18/2113 ,  G06F30/20 ,  G06N7/01

    Abstract: This disclosure involves generating graph data structures that model inter-feature dependencies for use with machine-learning models to predict end-user behavior. For example, a processing device receives an input dataset and a request to modify a first input feature of the input dataset. The processing device uses a graph data structure that models the inter-feature dependencies to modify the input dataset by propagating the modification of the first input feature to a second input feature dependent on the first input feature. The modification to the second input feature is a function of at least (a) the value of the first input feature and (b) a weight assigned to an edge linking the first input feature to the second input feature within the directed graph. The processing device then applies a trained machine-learning model to the modified input dataset to generate a prediction of an outcome.

    VIDEO MANIPULATION DETECTION
    3.
    发明公开
    VIDEO MANIPULATION DETECTION 审中-公开

    公开(公告)号：US20230410505A1

    公开(公告)日：2023-12-21

    申请号：US17845353

    申请日：2022-06-21

    Applicant: Adobe Inc.

    Inventor： Ritwik Sinha ,  Viswanathan Swaminathan ,  Trisha Mittal ,  John Philip Collomosse

    IPC: G06V20/40 ,  G06T7/00

    CPC classification number: G06V20/41 ,  G06V20/44 ,  G06T7/0002

    Abstract: Techniques for video manipulation detection are described to detect one or more manipulations present in digital content such as a digital video. A detection system, for instance, receives a frame of a digital video that depicts at least one entity. Coordinates of the frame that correspond to a gaze location of the entity are determined, and the detection system determines whether the coordinates correspond to a portion of an object depicted in the frame to calculate a gaze confidence score. A manipulation score is generated that indicates whether the digital video has been manipulated based on the gaze confidence score. In some examples, the manipulation score is based on at least one additional confidence score.

    SYSTEM AND METHODS FOR DIVERSITY AUDITING
    5.
    发明公开
    SYSTEM AND METHODS FOR DIVERSITY AUDITING 审中-公开

    公开(公告)号：US20230267764A1

    公开(公告)日：2023-08-24

    申请号：US17652026

    申请日：2022-02-22

    Applicant: ADOBE INC.

    Inventor： Md Mehrab Tanjim ,  Ritwik Sinha ,  Moumita Sinha ,  David Thomas Arbour ,  Sridhar Mahadevan

    IPC: G06V40/16

    CPC classification number: G06V40/172

    Abstract: Systems and methods for diversity auditing are described. The systems and methods include identifying a plurality of images; detecting a face in each of the plurality of images using a face detection network; classifying the face in each of the plurality of images based on a sensitive attribute using an image classification network; generating a distribution of the sensitive attribute in the plurality of images based on the classification; and computing a diversity score for the plurality of images based on the distribution.

    ACCURATE AND INTERPRETABLE RULES FOR USER SEGMENTATION
    6.
    发明申请
    ACCURATE AND INTERPRETABLE RULES FOR USER SEGMENTATION 有权

    公开(公告)号：US20220058503A1

    公开(公告)日：2022-02-24

    申请号：US17519935

    申请日：2021-11-05

    Applicant: Adobe Inc.

    Inventor： Ritwik Sinha ,  Virgil-Artimon Palanciuc ,  Pranav Ravindra Maneriker ,  Manish Dash ,  Tharun Mohandoss ,  Dhruv Singal

    IPC: G06N5/04 ,  G06N3/04 ,  G06N3/08

    Abstract: Various embodiments describe user segmentation. In an example, potential rules are generated by applying a frequency-based analysis to user interaction data points. Each of the potential rules includes a set of attributes of the user interaction data points and indicates that these data points belong to a segment of interest. An objective function is used to select an optimal set of rules from the potential rules for the segment of interest. The potential rules are used as variable inputs to the objective function and this function is optimized based on interpretability and accuracy parameters. Each rule from the optimal set is associated with a group of the segment of interest. The user interaction data points are segments into the groups by matching attributes of these data points with the rules.

    Fast and accurate rule selection for interpretable decision sets
    8.
    发明授权
    Fast and accurate rule selection for interpretable decision sets 有权

    公开(公告)号：US11704591B2

    公开(公告)日：2023-07-18

    申请号：US16353076

    申请日：2019-03-14

    Applicant: Adobe Inc.

    Inventor： Sunny Dhamnani ,  Dhruv Singal ,  Ritwik Sinha

    IPC: G06N20/00 ,  G06N5/025 ,  G06F16/901 ,  G06F18/243 ,  G06F18/2115 ,  G06N7/01

    CPC classification number: G06N20/00 ,  G06F16/9014 ,  G06F18/2115 ,  G06F18/24323 ,  G06N5/025 ,  G06N7/01

    Abstract: An IDS generator determines multiple classes for electronic data items. The IDS generator determines, for each class, a class-specific candidate ruleset. The IDS generator performs a differential analysis of each class-specific candidate ruleset. The differential analysis is based on differences between result values of a scoring objective function. In some cases, the differential analysis determines at least one of the differences based on additional data structures, such as an augmented frequent-pattern tree. A probability function based on the differences is compared to a threshold probability At least one testing ruleset is modified based on the comparison. The IDS generator determines, for each class, a class-specific optimized ruleset based on the differential analysis of each class-specific candidate ruleset. The IDS generator creates an optimized interpretable decision set based on combined class-specific optimized rulesets for the multiple classes.

    GENERATING AND EXECUTING AUTOMATIC SUGGESTIONS TO MODIFY DATA OF INGESTED DATA COLLECTIONS WITHOUT ADDITIONAL DATA INGESTION
    9.
    发明申请
    GENERATING AND EXECUTING AUTOMATIC SUGGESTIONS TO MODIFY DATA OF INGESTED DATA COLLECTIONS WITHOUT ADDITIONAL DATA INGESTION 有权

    公开(公告)号：US20220398230A1

    公开(公告)日：2022-12-15

    申请号：US17347133

    申请日：2021-06-14

    Applicant: Adobe Inc.

    Inventor： Ritwik Sinha ,  Saayan Mitra ,  Handong Zhao ,  Somdeb Sarkhel ,  Trevor Paulsen ,  William Brandon George

    IPC: G06F16/215 ,  G06F16/242 ,  G06N5/04 ,  G06N20/00

    Abstract: The present disclosure relates to systems, non-transitory computer-readable media, and methods for generating automatic suggestions to effectively modify the organization of an ingested data collection without destruction of the underlying raw data. In particular, in one or more embodiments, the disclosed systems utilize multiple machine learning models in sequence to determine likelihoods that the organizational structure of an ingested data collection should be modified in various ways. In response to generating these likelihoods, the disclosed systems generate corresponding automatic suggestions to modify the organization of the ingested data collection. In response to a detected selection of one or more of the automatic suggestions, the disclosed systems read data out of the ingested data collection in accordance with the selected automatic suggestions to effectively modify the organization of the ingested data collection.

    Utilizing one hash permutation and populated-value-slot-based densification for generating audience segment trait recommendations
    10.
    发明授权
    Utilizing one hash permutation and populated-value-slot-based densification for generating audience segment trait recommendations 有权

    公开(公告)号：US11109085B2

    公开(公告)日：2021-08-31

    申请号：US16367628

    申请日：2019-03-28

    Applicant: Adobe Inc.

    Inventor： Anup Rao ,  Yasin Abbasi Yadkori ,  Tung Mai ,  Ryan Rossi ,  Ritwik Sinha ,  Matvey Kapilevich ,  Alexandru Ionut Hodorogea

    IPC: G06F7/00 ,  G06F16/00 ,  H04N21/258 ,  H04N21/482 ,  H04N21/2668

    Abstract: The present disclosure relates to training a recommendation model to generate trait recommendations using one permutation hashing and populated-value-slot-based densification. In particular, the disclosed systems can train the recommendation model by computing sketch vectors corresponding to traits using one permutation hashing. The disclosed systems can then fill in unpopulated value slots of the sketch vectors using populated-value-slot-based densification. The disclosed systems can combine the resulting densified sketches to generate the trained recommendation model. For example, in some embodiments, the disclosed systems can combine the sketches by generating a plurality of locality sensitive hashing tables based on the sketches. In some embodiments, the disclosed systems generate a count sketch matrix based on the sketches and generate trait embeddings based on the count sketch matrix using spectral embedding. Based on the trait embeddings, the disclosed systems can utilize the recommendation model to flexibly and accurately determine the similarity between traits.

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