PATE framework for differentially private machine learning

Machine learning models can memorize fragments of their training data and return these fragments verbatim. I’ve seen instances, for example, where I believe an LLM returned phrases verbatim from this site. It’s easy to imagine how medical data might leak this way. How might you prevent this? And how might you do it in a […] The post PATE framework for differentially private machine learning first appeared on John D. Cook....

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