Patents by Inventor Samarth SIKAND

Samarth SIKAND has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20210224588
    Abstract: In some examples, recruitment process graph based unsupervised anomaly detection may include obtaining log data associated with a recruitment process for a plurality of candidates, and generating knowledge graphs and graph embeddings. The graph embeddings may be trained to include a plurality of properties such that graph embeddings of genuine candidate hires and fraudulent candidate hires are appropriately spaced in a vector space. The trained graph embeddings may be clustered to generate a plurality of embedding clusters that include a genuine candidate cluster, and a fraudulent candidate cluster. For a new candidate graph embedding for a new candidate, a determination may be made as to whether the new candidate graph embedding belongs to the genuine candidate cluster, to the fraudulent candidate cluster, or to an anomalous cluster, and instructions may be generated to respectively retain or suspend the new candidate.
    Type: Application
    Filed: January 19, 2021
    Publication date: July 22, 2021
    Applicant: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Samarth SIKAND, Venkatesh Subramanian, Neville Dubash, Sanjay Podder
  • Publication number: 20210166080
    Abstract: In some implementations, a device may receive a machine learning model to be tested. The device may process the machine learning model, with generalization testing methods, to determine generalization which identifies responsiveness of the machine learning model to varying inputs. The device may process the machine learning model, with robustness testing methods, to determine robustness which identifies responsiveness of the machine learning model to improper inputs. The device may process the machine learning model, with an interpretability testing method, to determine decisions of the machine learning model. The device may calculate a score for the machine learning model based on the generalization data, the robustness data, and the interpretability data. The device may perform one or more actions based on the score for the machine learning model.
    Type: Application
    Filed: December 1, 2020
    Publication date: June 3, 2021
    Inventors: Sanjay PODDER, Neville DUBASH, Nisha RAMACHANDRA, Raghotham M. RAO, Manish AHUJA, Samarth SIKAND
  • Patent number: 10997470
    Abstract: Systems, apparatuses, and methods are directed towards identifying that an adversarial patch image includes a plurality of pixels. The systems, apparatuses, and methods include dividing the adversarial patch image into a plurality of blocks, that each include a different group of the pixels in which the pixels are contiguous to each other, and assigning a first plurality of colors to the plurality of blocks to assign only one of the first plurality of colors to each pixel of one of the plurality of blocks.
    Type: Grant
    Filed: August 30, 2019
    Date of Patent: May 4, 2021
    Assignee: ACCENTURE GLOBAL SOLUTIONS LIMITED
    Inventors: Manish Ahuja, Samarth Sikand, Anurag Dwarakanath, Sanjay Podder
  • Publication number: 20210064938
    Abstract: Systems, apparatuses, and methods are directed towards identifying that an adversarial patch image includes a plurality of pixels. The systems, apparatuses, and methods include dividing the adversarial patch image into a plurality of blocks, that each include a different group of the pixels in which the pixels are contiguous to each other, and assigning a first plurality of colors to the plurality of blocks to assign only one of the first plurality of colors to each pixel of one of the plurality of blocks.
    Type: Application
    Filed: August 30, 2019
    Publication date: March 4, 2021
    Applicant: Accenture Global Solutions Limited
    Inventors: Manish Ahuja, Samarth Sikand, Anurag Dwarakanath, Sanjay Podder
  • Patent number: 10438118
    Abstract: A device may receive, from a user device, a request to verify a machine learning (ML) application using a metamorphic testing procedure. The device may determine a type of ML process used by the ML application, and may select one or more metamorphic relations (MRs), to be used for performing the metamorphic testing procedure, based on the type of ML process. The device may receive test data to be used to test the ML application, wherein the test data is based on the one or more MRs, and may perform, by using the one or more MRs and the test data, the metamorphic testing procedure to verify one or more aspects of the ML application. The device may generate a report that indicates whether the one or more aspects of the ML application have been verified and may provide the report for display on an interface of the user device.
    Type: Grant
    Filed: September 28, 2018
    Date of Patent: October 8, 2019
    Assignee: Accenture Global Solutions Limited
    Inventors: Anurag Dwarakanath, Sanjay Podder, Neville Dubash, Kishore P Durg, Manish Ahuja, Raghotham M Rao, Samarth Sikand, Jagadeesh Chandra Bose Rantham Prabhakara
  • Publication number: 20190108443
    Abstract: A device may receive, from a user device, a request to verify a machine learning (ML) application using a metamorphic testing procedure. The device may determine a type of ML process used by the ML application, and may select one or more metamorphic relations (MRs), to be used for performing the metamorphic testing procedure, based on the type of ML process. The device may receive test data to be used to test the ML application, wherein the test data is based on the one or more MRs, and may perform, by using the one or more MRs and the test data, the metamorphic testing procedure to verify one or more aspects of the ML application.
    Type: Application
    Filed: September 28, 2018
    Publication date: April 11, 2019
    Inventors: Anurag DWARAKANATH, Sanjay PODDER, Neville DUBASH, Kishore P. DURG, Manish AHUJA, Raghotham M. RAO, Samarth SIKAND, Jagadeesh Chandra BOSE RANTHAM PRABHAKARA