Invention Grant
- Patent Title: Generation of synthetic data using agent-based simulations
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Application No.: US17142097Application Date: 2021-01-05
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Publication No.: US11847390B2Publication Date: 2023-12-19
- Inventor: Francisco Gutierrez , Matthew Tomaszewicz , Sandeep Narayanaswami , Eiran Shalev
- Applicant: Capital One Services, LLC
- Applicant Address: US VA McLean
- Assignee: Capital One Services, LLC
- Current Assignee: Capital One Services, LLC
- Current Assignee Address: US VA McLean
- Agency: Banner & Witcoff, Ltd.
- Main IPC: G06F30/20
- IPC: G06F30/20 ; G06F30/27 ; G06F7/58 ; G06F17/18

Abstract:
A system, method, and computer-readable medium for generating factual and/or counterfactual data are described. This may have the effect of improving the complexity of data available for training machine learning models. The models may include, but not limited to, a probabilistic graphical model (PGM) and/or an agent-based model (ABM). Further aspects may provide for scrubbing actual data to create a data model that does not reveal the content of the underlying source data. Yet further aspects may provide for validating a data model.
Public/Granted literature
- US20220215141A1 Generation of Synthetic Data using Agent-Based Simulations Public/Granted day:2022-07-07
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