학술논문

Low Resource Vs High Resource solutions for Federated learning sentiment analysis
Document Type
Conference
Source
2023 IEEE International Conference on Consumer Electronics (ICCE) Consumer Electronics (ICCE), 2023 IEEE International Conference on. :1-3 Jan, 2023
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Training
Sentiment analysis
Analytical models
Federated learning
Bit error rate
Consumer electronics
BERT
RNN
Language
ISSN
2158-4001
Abstract
In this paper we demonstrate the use of RNN and BERT models with a federated learning framework. We evaluate the performance of both the models and compare the trade-off between training time, model parameters and accuracy.