Code and Data Repository for PPFL: A Personalized Federated Learning Framework for Heterogeneous Population

This archive is distributed in association with the INFORMS Journal on Computing under the MIT License.

Authors

Hao Di (ORCID: https://orcid.org/0009-0004-1846-9787)
Yi Yang (ORCID: https://orcid.org/0009-0009-4106-4581)

Publication Details

Journal: INFORMS journal on computing
Published: 2025-08-04
DOI: https://doi.org/10.1287/ijoc.2023.0376.cd
Primary Topic: Privacy-Preserving Technologies in Data
Type: article
Field-Weighted Citation Impact: 0.00

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article

Code and Data Repository for PPFL: A Personalized Federated Learning Framework for Heterogeneous Population

Hao Di, Yi Yang

Aug 4, 2025

INFORMS journal on computing

Privacy-Preserving Technologies in Data

article

Code and Data Repository for PPFL: A Personalized Federated Learning Framework for Heterogeneous Population

Hao Di, Yi Yang

August 4, 2025article en

Abstract

This archive is distributed in association with the INFORMS Journal on Computing under the MIT License.

INFORMS journal on computing

Openalex Percentile: Top 90%

Privacy-Preserving Technologies in Data

DOI Source OpenAlex

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Code and Data Repository for PPFL: A Personalized Federated Learning Framework for Heterogeneous Population — Hao Di, Yi Yang · INFORMS journal on computing (2025) | TGRS Research Map | TGRS