Exploiting Unlabeled Data in Smart Cities using Federated Learning

01/10/2020
by   Abdullatif Albaseer, et al.
0

Privacy concerns are considered one of the main challenges in smart cities as sharing sensitive data brings threatening problems to people's lives. Federated learning has emerged as an effective technique to avoid privacy infringement as well as increase the utilization of the data. However, there is a scarcity in the amount of labeled data and an abundance of unlabeled data collected in smart cities, hence there is a need to use semi-supervised learning. We propose a semi-supervised federated learning method called FedSem that exploits unlabeled data. The algorithm is divided into two phases where the first phase trains a global model based on the labeled data. In the second phase, we use semi-supervised learning based on the pseudo labeling technique to improve the model. We conducted several experiments using traffic signs dataset to show that FedSem can improve accuracy up to 8 the learning process.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/12/2021

FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning

Federated Learning has shown great potentials for the distributed data u...
research
12/05/2019

Collective Learning

In this paper, we introduce the concept of collective learning (CL) whic...
research
02/26/2020

A Survey towards Federated Semi-supervised Learning

The success of Artificial Intelligence (AI) should be largely attributed...
research
08/21/2021

SemiFed: Semi-supervised Federated Learning with Consistency and Pseudo-Labeling

Federated learning enables multiple clients, such as mobile phones and o...
research
10/09/2018

Enabling Cognitive Smart Cities Using Big Data and Machine Learning: Approaches and Challenges

The development of smart cities and their fast-paced deployment is resul...
research
07/08/2021

A Federated Semi-Supervised Learning Approach for Network Traffic Classification

Network traffic classification, a task to classify network traffic and i...
research
08/26/2020

Benchmarking Semi-supervised Federated Learning

Federated learning promises to use the computational power of edge devic...

Please sign up or login with your details

Forgot password? Click here to reset