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Utility is all you need: fidelity-agnostic synthetic data generation

2024-10-24

Abstract excerpt

<title>Abstract</title> <p>Synthesizing data has been popularized as a method to publish useful datasets in a privacy-aware manner, making it useful across a range of scientific domains involving human subjects like health, social, financial, and other applied sciences. It is typically generated by sampling from algorithms which mimic the probability distribution of real datasets, thereby maximizing statistical s...

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Literature Corpus work: b0743b63-59fa-5a47-bf57-73aebee4bbfe
DOI: 10.21203/rs.3.rs-5319537/v1

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