# FedEasy : Federated learning with ease

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/fedeasy-federated-learning-with-ease/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Majid Kundroo,Ghani Haider,Nguyen Lu Dang Khoa,Abdul Wahab Mamond,Tae‐Hong Kim |
| Citations | 8 |
| DOI | 10.1016/j.softx.2025.102276 |
| Fields | Computer Science |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1016/j.softx.2025.102276 |
| OpenAlex ID | https://openalex.org/W4412958438 |
| Type | software-paper |
| Year | 2025 |

## Paper authors

- [Majid Kundroo](https://scholariq.org/researchers/majid-kundroo/)

## 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/)
- [Cryptography and Data Security](https://scholariq.org/topics/cryptography-and-data-security/)
- [Stochastic Gradient Optimization Techniques](https://scholariq.org/topics/stochastic-gradient-optimization-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.