Vertical federated learning: Concepts, advances, and challenges
Vertical Federated Learning (VFL) is a federated learning setting where multiple parties with
different features about the same set of users jointly train machine learning models without …
different features about the same set of users jointly train machine learning models without …
Smart electric vehicle charging in the era of internet of vehicles, emerging trends, and open issues
The Internet of Vehicles (IoV), where people, fleets of electric vehicles (EVs), utility, power
grids, distributed renewable energy, and communications and computing infrastructures are …
grids, distributed renewable energy, and communications and computing infrastructures are …
A review on intelligent energy management systems for future electric vehicle transportation
Over the last few years, Electric Vehicles (EVs) have been gaining interest as a result of their
ability to reduce vehicle emissions. Develo** an intelligent system to manage EVs …
ability to reduce vehicle emissions. Develo** an intelligent system to manage EVs …
Edge intelligence in Smart Grids: A survey on architectures, offloading models, cyber security measures, and challenges
The rapid development of new information and communication technologies (ICTs) and the
deployment of advanced Internet of Things (IoT)-based devices has led to the study and …
deployment of advanced Internet of Things (IoT)-based devices has led to the study and …
Efficient federated item similarity model for privacy-preserving recommendation
X Ding, G Li, L Yuan, L Zhang, Q Rong - Information Processing & …, 2023 - Elsevier
Previous federated recommender systems are based on traditional matrix factorization,
which can improve personalized service but are vulnerable to gradient inference attacks …
which can improve personalized service but are vulnerable to gradient inference attacks …
Secure and privacy-preserving decentralized federated learning for personalized recommendations in consumer electronics using blockchain and homomorphic …
BB Gupta, A Gaurav, V Arya - IEEE Transactions on Consumer …, 2023 - ieeexplore.ieee.org
Over the past few years, personalized recommendations have emerged as a fundamental
component of the consumer electronics sector. The rise of decentralized federated learning …
component of the consumer electronics sector. The rise of decentralized federated learning …
A comprehensive survey on privacy-preserving techniques in federated recommendation systems
Big data is a rapidly growing field, and new developments are constantly emerging to
address various challenges. One such development is the use of federated learning for …
address various challenges. One such development is the use of federated learning for …
State-of-the-art with numerical analysis on electric fast charging stations: infrastructures, standards, techniques, and challenges
Replacement of conventional gasoline vehicles by Electric Vehicles (EVs) attracts the
attention of stakeholders, utilities, and customers. However, to meet this urgent need of EVs …
attention of stakeholders, utilities, and customers. However, to meet this urgent need of EVs …
Crossing roads of federated learning and smart grids: Overview, challenges, and perspectives
Consumer's privacy is a main concern in Smart Grids (SGs) due to the sensitivity of energy
data, particularly when used to train machine learning models for different services. These …
data, particularly when used to train machine learning models for different services. These …
Match maximization of vehicle-to-vehicle energy charging with double-sided auction
The future Intelligent Transportation System (ITS) will rely heavily on the advancement of the
Internet of Things (IoT). Indeed, the IoT infrastructure paves the way toward connecting …
Internet of Things (IoT). Indeed, the IoT infrastructure paves the way toward connecting …