HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data Synthesization
Summary: HRNet differentially privately synthesizes human mobility via hierarchical location encoding, multi-resolution multi-task learning, and private pre-training. Experiments show improved utility–privacy trade-offs over prior mobility synthesis methods. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Shun Takagi (Kyoto University)
- 2. Li Xiong (Emory University)
- 3. Fumiyuki Kato (Kyoto University)
- 4. Yang Cao (Tokyo Institute of Technology)
- 5. Masatoshi Yoshikawa (Osaka Seikei University)
BibTeX Citation
@article{takagi_vldb24,
title = {{HRNet: Differentially Private Hierarchical and Multi-Resolution Network for Human Mobility Data Synthesization}},
author = {Takagi, Shun and Xiong, Li and Kato, Fumiyuki and Cao, Yang and Yoshikawa, Masatoshi},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {11},
pages = {3058--3071},
doi = {10.14778/3681954.3681983},
url = {https://doi.org/10.14778/3681954.3681983},
year = {2024}
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 276 | Towards Practical Differential Privacy for SQL Queries | 2018 | VLDB | 0.0002234348 |
| 1,324 | PrivTree: A Differentially Private Algorithm for Hierarchical Decompositions | 2016 | SIGMOD | 0.00011023355 |
| 3,938 | DPT: Differentially Private Trajectory Synthesis Using Hierarchical Reference Systems | 2015 | VLDB | 6.9153613e-05 |
| 6,701 | A Deep Generative Model for Trajectory Modeling and Utilization | 2023 | VLDB | 5.7055034e-05 |
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