Assessment of differentially private synthetic data for utility and fairness in end-to-end machine learning pipelines for tabular data

• Mayana Pereira ,

  Roles Conceptualization, Data curation, Formal analysis, Methodology, Visualization, Writing – original draft

  * E-mail: mayana.wanderley@microsoft.com

  Affiliations AI for Good Research Lab, Microsoft, Redmond, Washington, United States of America, Department of Electrical Engineering, University of Brasilia, Brasilia, Brazil

  https://orcid.org/0000-0001-8636-8882

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• Meghana Kshirsagar,

  Roles Conceptualization, Formal analysis, Writing – original draft

  Affiliation AI for Good Research Lab, Microsoft, Redmond, Washington, United States of America

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• Sumit Mukherjee,

  Roles Conceptualization, Formal analysis, Writing – original draft

  Affiliation INSITRO, San Francisco, CA, United States of America

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• Rahul Dodhia,

  Roles Formal analysis, Validation, Writing – review & editing

  Affiliation AI for Good Research Lab, Microsoft, Redmond, Washington, United States of America

  https://orcid.org/0000-0003-3812-3906

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• Juan Lavista Ferres,

  Roles Formal analysis, Validation, Writing – review & editing

  Affiliation AI for Good Research Lab, Microsoft, Redmond, Washington, United States of America

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• Rafael de Sousa

  Roles Methodology, Supervision, Writing – review & editing

  Affiliation Department of Electrical Engineering, University of Brasilia, Brasilia, Brazil

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