• Patent Title: Robust model performance across disparate sub-groups within a same group
  • Application No.: US17434849
    Application Date: 2020-09-30
  • Publication No.: US12248854B2
    Publication Date: 2025-03-11
  • Inventor: Joshua Patrick GardnerWei Huang
  • Applicant: Google LLC
  • Applicant Address: US CA Mountain View
  • Assignee: Google LLC
  • Current Assignee: Google LLC
  • Current Assignee Address: US CA Mountain View
  • Agency: Fish & Richardson P.C.
  • International Application: PCT/US2020/053378 WO 20200930
  • International Announcement: WO2022/071929 WO 20220407
  • Main IPC: G06N20/00
  • IPC: G06N20/00
Robust model performance across disparate sub-groups within a same group
Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for reducing the difference in performance of a model across groups and sub-groups within the same group of users with similar characteristics for providing digital components. Methods can include identifying, a loss function that generates a loss representing a measure of performance the model seeks to optimize during training. The loss function is modified by adding an additional term to the loss function. The model is trained using the modified loss function. A request for digital component is received that includes a user group identifier. The model generates one or more user characteristics based on which one or more digital components are selected and transmitted to the client device of the user.
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