Invention Grant
- Patent Title: Coordinated multiple worker node causal inference framework
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Application No.: US16906759Application Date: 2020-06-19
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Publication No.: US11574216B2Publication Date: 2023-02-07
- Inventor: Teresa Sheausan Tung , Mohamad Mehdi Nasr-Azadani , Yao A. Yang , Zaid Tashman , Maziyar Baran Pouyan
- Applicant: Accenture Global Solutions Limited
- Applicant Address: IE Dublin
- Assignee: Accenture Global Solutions Limited
- Current Assignee: Accenture Global Solutions Limited
- Current Assignee Address: IE Dublin
- Agency: Crowell & Moring LLP
- Main IPC: G06F15/16
- IPC: G06F15/16 ; G06N5/04 ; G06N20/00

Abstract:
A systems implements a gradient descent calculation, regression calculation, or other machine learning calculation on a dataset (e.g., a global dataset) using a coordination node including coordination circuitry that coordinates multiple worker nodes to create a distributed calculation architecture. In some cases, the worker nodes each hold a portion of the dataset and operate on their respective portion. In some cases, the gradient descent calculation, regression calculation, or other machine learning calculation is used to implement a targeted maximum likelihood scheme for causal inference estimation. The targeted maximum likelihood scheme may be used to conduct causal analysis of the observational data.
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