Add to ORKGSynthetic data generation is a powerful tool for privacy protection when considering public release of record-level data files. Initially proposed about three decades ago, it has generated significant research and application interest. To meet the pressing demand of data privacy protection in a variety of contexts, the field needs more researchers and practitioners. This review provides a comprehensive introduction to synthetic data, including technical details of their generation and evaluation. Our review also addresses the challenges and limitations of synthetic data, discusses practical applications, and provides thoughts for future work
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
In a world where artificial intelligence and data science become omnipresent, data sharing is increa...
This explainer document aims to provide an overview of the current state of the rapidly expanding wo...
This is the final version. Available on open access from SAGE Publications via the DOI in this recor...
These talks were presented for the Privacy Day Webinar 2022 sponsored by the American Statistical As...
Synthetic data has gained significant momentum thanks to sophisticated machine learning tools that e...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
AI-based data synthesis has seen rapid progress over the last several years and is increasingly reco...
When processing data that contains sensitive information, careful consideration is required with reg...
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
In a world where artificial intelligence and data science become omnipresent, data sharing is increa...
This explainer document aims to provide an overview of the current state of the rapidly expanding wo...
This is the final version. Available on open access from SAGE Publications via the DOI in this recor...
These talks were presented for the Privacy Day Webinar 2022 sponsored by the American Statistical As...
Synthetic data has gained significant momentum thanks to sophisticated machine learning tools that e...
Data Study Groups are week-long events at The Alan Turing Institute bringing together some of the co...
Synthetic data has been advertised as a silver-bullet solution to privacy-preserving data publishing...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
When processing data that contains sensitive information, careful consideration is required with reg...
AI-based data synthesis has seen rapid progress over the last several years and is increasingly reco...
When processing data that contains sensitive information, careful consideration is required with reg...
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
How can we share sensitive datasets in such a way as to maximize utility while simultaneously safegu...
In a world where artificial intelligence and data science become omnipresent, data sharing is increa...