About this document

3Privacy-Preserving Federated Learning and Its Application To Natural Language Processing by f2025436043 is a document available to read on EtoBox.

The document presents a privacy-preserving Federated Learning (FL) framework aimed at training machine learning models on sensitive local data, particularly in natural language processing (NLP) applications. It utilizes techniques such as bitwise quantization, local differential privacy, and feature hashing to ensure privacy while enabling effective model training on edge devices. The framework demonstrates its effectiveness through sentiment analysis and rating prediction tasks, showing that it can maintai

Author

f2025436043

Language

EN