Invention Grant
- Patent Title: Learning robust predictors using game theory
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Application No.: US17115489Application Date: 2020-12-08
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Publication No.: US12282836B2Publication Date: 2025-04-22
- Inventor: Kartik Ahuja , Karthikeyan Shanmugam , Kush Raj Varshney , Amit Dhurandhar
- Applicant: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Applicant Address: US NY Armonk
- Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
- Current Assignee Address: US NY Armonk
- Agent Rakesh Roy
- Main IPC: G06N20/20
- IPC: G06N20/20 ; G06N7/00

Abstract:
A method, computer system, and a computer program product for invariant risk minimization games is provided. The present invention may include defining a plurality of environment-specific classifiers corresponding to a plurality of environments. The present invention may also include constructing an ensemble classifier associated with the plurality of environment-specific classifiers. The present invention may further include initiating a game including a plurality of players corresponding to the plurality of environments. The present invention may also include calculating a nash equilibrium of the initiated game. The present invention may further include determining an ensemble predictor based on the calculated nash equilibrium. The present invention may include deploying the determined ensemble predictor associated with the calculated nash equilibrium to make predictions in a new environment.
Public/Granted literature
- US20220180254A1 LEARNING ROBUST PREDICTORS USING GAME THEORY Public/Granted day:2022-06-09
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