# PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/pfa-privacy-preserving-federated-adaptation-for-effective-model-personalization/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Bingyan Liu,Yao Guo,Xiangqun Chen |
| Citations | 114 |
| DOI | 10.1145/3442381.3449847 |
| Fields | Computer Science,Engineering |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1145/3442381.3449847 |
| OpenAlex ID | https://openalex.org/W3156024711 |
| Type | conference-paper |
| Year | 2021 |

## Paper authors

- [Yao Guo](https://scholariq.org/researchers/yao-guo/)

## Paper primary topic

- [Privacy-Preserving Technologies in Data](https://scholariq.org/topics/privacy-preserving-technologies-in-data/)

## Paper topics

- [Privacy-Preserving Technologies in Data](https://scholariq.org/topics/privacy-preserving-technologies-in-data/)
- [Traffic Prediction and Management Techniques](https://scholariq.org/topics/traffic-prediction-and-management-techniques/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.