Differential privacy is the statistical science of trying to learn as much as possible about a group while learning as little as possible about any individual in it. In an age of big data analysis and machine learning, differential privacy is a fast growing area of research for protecting people’s privacy interests.
Register for this free ASA webinar sponsored by the Privacy & Confidentiality Committee and learn the statistical approach and fundamental principles of this data protection method for protecting privacy interests.
Registration: This webinar is free, but registration is required:
https://www.amstat.org/ASA/Education/Web-Based-Lectures.aspx.
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Jacob Bournazian
[chair]
[Privacy and Confidentiality Committee
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