Work

Approximate Computing for Federated Learning

Year: 2025

Type: article

Abstract: We explore the usage of approximate computing to enhance the security and privacy of Federated Learning against training data reconstruction attacks.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.17901250

Author: Tarchoun, Bilel

Institutions: Centre National de la Recherche Scientifique, Institut d'Electronique, de Microélectronique et de Nanotechnologie

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: European Commission

Award: Edge AI Technologies for Optimised Performance Embedded Processing

OpenAlex ID: W7116096258

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