Invention Grant
- Patent Title: Computer systems for detecting training data usage in generative models
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Application No.: US16140022Application Date: 2018-09-24
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Publication No.: US11366982B2Publication Date: 2022-06-21
- Inventor: Martin Haerterich , Benjamin Hilprecht , Daniel Bernau
- Applicant: SAP SE
- Applicant Address: DE Walldorf
- Assignee: SAP SE
- Current Assignee: SAP SE
- Current Assignee Address: DE Walldorf
- Agency: Schwegman Lundberg & Woessner, P.A.
- Main IPC: G06K9/62
- IPC: G06K9/62 ; G06V10/50 ; G06N20/00

Abstract:
Various examples are directed to systems and methods for detecting training data for a generative model. A computer system may access generative model sample data and a first test sample. The computer system may determine whether a first generative model sample of the plurality of generative model samples is within a threshold distance of the first test sample and whether a second generative model sample of the plurality of generative model samples is within the threshold distance of the first test sample. The computer system may determine that a probability that the generative model was trained with the first test sample is greater than or equal to a threshold probability based at least in part on whether the first generative model sample is within the threshold distance of the first test sample, the determining also based at least in part on whether the second generative model sample is within the threshold distance of the first test sample.
Public/Granted literature
- US20200097763A1 COMPUTER SYSTEMS FOR DETECTING TRAINING DATA USAGE IN GENERATIVE MODELS Public/Granted day:2020-03-26
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