Patents Assigned to Faire (NI)Limited
  • Patent number: 12367587
    Abstract: A method includes generating a plurality of binary feature maps containing a set of feature map values including a first binary value and/or a second binary value, by at least converting each input value of a set of input values of a plurality of input feature vectors to the first binary value when the corresponding input value is the zero value or the second binary value when the corresponding input value is the non-zero value. The method includes segmenting the plurality of binary feature maps into a plurality of segments representing behavior profiles. Each segment includes at least one subsegment in which the set of feature map values is the same for all binary feature maps in the at least one subsegment. The method includes predicting, based on a segment of the plurality of segments, a specific outcome. Related methods and articles of manufacture are also disclosed.
    Type: Grant
    Filed: January 3, 2023
    Date of Patent: July 22, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Yuchen Chen, Scott Michael Zoldi
  • Patent number: 12353929
    Abstract: A data object from a data source is received by a distributed process in a data stream. The distributed process has a sequence of categories, each category containing one or more tasks that operate on the data object. The data object includes files that can be processed by the tasks. If the task is able to operate on the data object, then the data object is passed to the task. If the task is unable to operate on the data object, then the files in the data object are passed to a file staging area of the distributed process and stored in memory. The files in the file staging area are passed, in sequence, from the file staging area to the task that was unable to operate on the data object. The data object is outputted to a next category or data sink after being operated on by the task.
    Type: Grant
    Filed: January 17, 2024
    Date of Patent: July 8, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Shalini Raghavan, Tom J. Traughber, George Vanecek, Jr.
  • Patent number: 12353315
    Abstract: Software validation systems, products, and methods for determining a plurality of test scenarios for a software code under test. The test scenarios may be defined based on at least one of values assigned to one or more variables declared in the software code, relationships defined between the one or more variables, and execution paths leading to one or more outcomes based on the values and the relationships, in response to the software code being executed. At least two or more test scenarios, from among the plurality of test scenarios, are consolidated into a first test scenario based on values defined in a modifiable script.
    Type: Grant
    Filed: May 16, 2022
    Date of Patent: July 8, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventor: Sowmya Pissay Krupashankar
  • Publication number: 20250181993
    Abstract: A system and method includes obtaining an incumbent model and a candidate model, generating a plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the incumbent model based on assessing model output data of the incumbent model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the candidate model based on assessing model output data of the candidate model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for the candidate model, a disparity-mitigating model viability score, and displaying, via a graphical user interface, a representation of the candidate model in association with the disparity-mitigating model viability sc
    Type: Application
    Filed: February 6, 2025
    Publication date: June 5, 2025
    Applicant: Fairness-as-a-Service, Inc.
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Patent number: 12282498
    Abstract: Systems and methods are provided for accessing a database of records to identify a set of records represented by one or more nodes in a graph model. A connection between a first node and a second node in the one or more nodes is monitored to determine an association between a first record, represented by the first node, and a second record, represented by the second node. The set of records may be partitioned into a plurality of groups. For at least a first group, including a first set of records, it may be determined whether two or more records in the first group are related. In response to determining that the two or more records in the first group are related, a first group identifier may be assigned to the two or more records.
    Type: Grant
    Filed: July 14, 2020
    Date of Patent: April 22, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventor: Brent Farrell
  • Patent number: 12248858
    Abstract: A system and method includes obtaining an incumbent model and a candidate model, generating a plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the incumbent model based on assessing model output data of the incumbent model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the candidate model based on assessing model output data of the candidate model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for the candidate model, a disparity-mitigating model viability score, and displaying, via a graphical user interface, a representation of the candidate model in association with the disparity-mitigating model viability sc
    Type: Grant
    Filed: June 12, 2024
    Date of Patent: March 11, 2025
    Assignee: Fairness-as-a-Service, Inc.
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Patent number: 12236353
    Abstract: Computer-implemented machines, systems and methods for providing insights about misalignment in a latent space of a machine learning model. A method includes initializing a second weight matrix of a second artificial neural network based on a first weight matrix from a first artificial neural network. The method further includes applying transfer learning between the first artificial neural network and the second artificial neural network. The method further includes comparing the first latent space with the second latent space. The method further includes determining, responsive to the comparing, a first score indicating alignment of the first latent space and the second latent space. The method further includes determining, and responsive to the first score satisfying a threshold, an appropriateness of the machine learning model.
    Type: Grant
    Filed: December 14, 2020
    Date of Patent: February 25, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott M. Zoldi, Jeremy Schmitt, Qing Liu
  • Patent number: 12229314
    Abstract: A method, a system, and a computer program product for generating a refined synthetic data from one or more sources of data. One or more source data are received from one or more data sources. One or more encoded source data are generated from the one or more source data. A synthetic data is generated by decoding one or more encoded source data. One or more variables in the synthetic data are selected and one or more predetermined identifiability values and one or more predetermined anonymity values are associated with them. The generated synthetic data including the selected variables is decoded using associated one or more predetermined identifiability values and one or more predetermined anonymity values. The decoded synthetic data is outputted.
    Type: Grant
    Filed: May 7, 2022
    Date of Patent: February 18, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Christopher Allan Ralph, Gerald Fahner
  • Patent number: 12197511
    Abstract: A method, a system, and a computer program product for generating an interpretable set of features. One or more search parameters and one or more constraints on one or more search parameters for searching data received from one or more data sources are defined. The data received from one or more data sources is searched using the defined search parameters and constraints. One or more first features are extracted from the searched data. The first features are associated with one or more predictive score values. The searching is repeated in response to receiving a feedback data responsive to the extracted first features. One or more second features resulting from the repeated searching are generated.
    Type: Grant
    Filed: January 17, 2024
    Date of Patent: January 14, 2025
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Christopher Allan Ralph, Gerald Fahner, Liang Meng
  • Publication number: 20240428133
    Abstract: A system and method includes obtaining an incumbent model and a candidate model, generating a plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the incumbent model based on assessing model output data of the incumbent model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for each synthetic model input dataset, a model performance efficacy metric and a model fairness efficacy metric for the candidate model based on assessing model output data of the candidate model that corresponds to each respective synthetic model input dataset of the plurality of synthetic model input datasets, computing, for the candidate model, a disparity-mitigating model viability score, and displaying, via a graphical user interface, a representation of the candidate model in association with the disparity-mitigating model viability sc
    Type: Application
    Filed: June 12, 2024
    Publication date: December 26, 2024
    Applicant: Fairness-as-a-Service, Inc.
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Patent number: 12158871
    Abstract: A system and method for analyzing coverage, bias and model explanations in large dimensional modeling data includes discretizing three or more variables of a dataset to generate a discretized phase space represented as a grid of a plurality of cells, the dataset comprising a plurality of records, each record of the plurality of records having a value and a unique identifier (ID). A grid transformation is applied to each record in the dataset to assign each record to a cell of the plurality of cells of the grid according to the grid transformation. A grid index is generated to reference each cell using a discretized feature vector. A grid storage for storing the records assigned to each cell of the grid is then created. The grid storage using the ID of each record as a reference to each record and the discretized feature vector as a key to each cell.
    Type: Grant
    Filed: May 10, 2022
    Date of Patent: December 3, 2024
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Scott Michael Zoldi, Shafi Ur Rahman
  • Patent number: 12137636
    Abstract: An implement for moving plant material lying in a field including a frame, a plurality of rake wheels rotatably mounted on the frame, and a plurality of support wheels to support the frame in an elevated condition. The implement may have a plurality of configurations, and may include a merge configuration configured to merge windrows of plant material on the field surface by lateral displacement of the plant material on the field surface. The plurality of configurations may include a turn configuration configured to turn the plant material on the field surface with a degree of lateral movement of the plant material on the field surface. The plurality of configurations may include a fluff configuration configured to lift plant material off of the field surface without lateral displacement of the plant material on the field surface.
    Type: Grant
    Filed: December 30, 2020
    Date of Patent: November 12, 2024
    Assignee: Fair Manufacturing, Inc.
    Inventors: Ethen D. Wentz, Daniel L. Crick
  • Patent number: 12039457
    Abstract: A system and method includes generating approximate distributions for distinct classes of data samples; computing a first partial Jensen-Shannon (JS) divergence and a second partial JS divergence based on the approximate distribution of the disparity affected class of data samples with reference to the approximate distribution of the control class of data samples; computing a disparity divergence based on the first partial JS divergence and the second partial JS divergence; generating a distribution-matching term based on the disparity divergence, wherein the distribution-matching term mitigates an inferential disparity between the control class of data samples and the disparity affected class of data samples during a training of an unconstrained artificial neural network; constructing a disparity-constrained loss function based on augmenting a target loss function with the distribution-matching term; and transforming the unconstrained ANN to a disparity-constrained ANN based on a training of the unconstraine
    Type: Grant
    Filed: December 27, 2023
    Date of Patent: July 16, 2024
    Assignee: Fairness-as-a-Service, Inc.
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Publication number: 20240135186
    Abstract: A system and method includes generating approximate distributions for distinct classes of data samples; computing a first partial Jensen-Shannon (JS) divergence and a second partial JS divergence based on the approximate distribution of the disparity affected class of data samples with reference to the approximate distribution of the control class of data samples; computing a disparity divergence based on the first partial JS divergence and the second partial JS divergence; generating a distribution-matching term based on the disparity divergence, wherein the distribution-matching term mitigates an inferential disparity between the control class of data samples and the disparity affected class of data samples during a training of an unconstrained artificial neural network; constructing a disparity-constrained loss function based on augmenting a target loss function with the distribution-matching term; and transforming the unconstrained ANN to a disparity-constrained ANN based on a training of the unconstraine
    Type: Application
    Filed: December 27, 2023
    Publication date: April 25, 2024
    Applicant: Fairness-as-a-Service, Inc.
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Patent number: 11966873
    Abstract: Computer-implemented methods, systems and products for analytics and discovery of patterns or signals. The method includes a set of operations or steps, including collecting data from a plurality of data sources, the data having a plurality of associated data types, and filtering the collected data based on identifying viable data sources from which the data is collected. The method further includes prioritizing discovery objectives based on analyzing the filtering results, and enriching the filtered collected data from viable data sources according to the prioritized discovery objectives. The method further includes extracting one or more signals from the enriched data using one or more machine learning mechanisms in combination with qualified subject matter expertise input, and graphically displaying the extracted signals in a meaningful way to a human operator such that the human operator is enabled to understand importance of extracted signals.
    Type: Grant
    Filed: April 18, 2022
    Date of Patent: April 23, 2024
    Assignee: Fair Isaac Corporation
    Inventors: Mary Krone, Ryan Weber, Ana Paula Azevedo Travassos, Laura Waterbury, Paulo Mei, Mayumi Assato, Shubham Kedia, Nitin Basant, Chisoo Lyons
  • Patent number: 11934960
    Abstract: A system and method includes generating approximate distributions for distinct classes of data samples; computing a first partial Jensen-Shannon (JS) divergence and a second partial JS divergence based on the approximate distribution of the disparity affected class of data samples with reference to the approximate distribution of the control class of data samples; computing a disparity divergence based on the first partial JS divergence and the second partial JS divergence; generating a distribution-matching term based on the disparity divergence, wherein the distribution-matching term mitigates an inferential disparity between the control class of data samples and the disparity affected class of data samples during a training of an unconstrained artificial neural network; constructing a disparity-constrained loss function based on augmenting a target loss function with the distribution-matching term; and transforming the unconstrained ANN to a disparity-constrained ANN based on a training of the unconstraine
    Type: Grant
    Filed: May 1, 2023
    Date of Patent: March 19, 2024
    Assignee: Fairness-as-a-Service
    Inventors: John Wickens-Lamb Merrill, Kareem Saleh, Mark Eberstein
  • Patent number: 11900181
    Abstract: A data object from a data source is received by a distributed process in a data stream. The distributed process has a sequence of categories, each category containing one or more tasks that operate on the data object. The data object includes files that can be processed by the tasks. If the task is able to operate on the data object, then the data object is passed to the task. If the task is unable to operate on the data object, then the files in the data object are passed to a file staging area of the distributed process and stored in memory. The files in the file staging area are passed, in sequence, from the file staging area to the task that was unable to operate on the data object. The data object is outputted to a next category or data sink after being operated on by the task.
    Type: Grant
    Filed: April 28, 2021
    Date of Patent: February 13, 2024
    Assignee: FAIR ISAAC CORPORATION
    Inventors: Shalini Raghavan, Tom J. Traughber, George Vanecek, Jr.
  • Patent number: 11886512
    Abstract: A method, a system, and a computer program product for generating an interpretable set of features. One or more search parameters and one or more constraints on one or more search parameters for searching data received from one or more data sources are defined. The data received from one or more data sources is searched using the defined search parameters and constraints. One or more first features are extracted from the searched data. The first features are associated with one or more predictive score values. The searching is repeated in response to receiving a feedback data responsive to the extracted first features. One or more second features resulting from the repeated searching are generated.
    Type: Grant
    Filed: May 7, 2022
    Date of Patent: January 30, 2024
    Assignee: Fair Isaac Corporation
    Inventors: Christopher Allan Ralph, Gerald Fahner, Liang Meng
  • Patent number: D1014911
    Type: Grant
    Filed: November 8, 2021
    Date of Patent: February 20, 2024
    Assignee: VEJA FAIR TRADE SARL
    Inventor: Sebastien Kopp
  • Patent number: D1028193
    Type: Grant
    Filed: November 19, 2021
    Date of Patent: May 21, 2024
    Assignee: Fair Game Group LLC
    Inventor: Bradley Gleaton