Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy-Reference-Cited by-同舟云学术

Generating synthetic mobility data for a realistic population with RNNs to improve utility and privacy

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 37th ACM/SIGAPP Symposium on Applied Computing
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Author:

Berke Alex¹,Doorley Ronan¹,Larson Kent¹,Moro Esteban¹

Affiliation:

1. MIT Media Lab

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3477314.3507230

Reference21 articles.

1. A case study

2. Human mobility: Models and applications

3. Synthesizing Plausible Privacy-Preserving Location Traces

4. U.S. Census Bureau. 2019. American Community Survey 2014--2018 5-year Estimates. https://data.census.gov/cedsci/table. U.S. Census Bureau. 2019. American Community Survey 2014--2018 5-year Estimates. https://data.census.gov/cedsci/table.

5. Differentially private sequential data publication via variable-length n-grams

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