Decentralized federated learning: Fundamentals, state of the art, frameworks, trends, and challenges
In recent years, Federated Learning (FL) has gained relevance in training collaborative
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
models without sharing sensitive data. Since its birth, Centralized FL (CFL) has been the …
A survey on deep learning for human mobility
The study of human mobility is crucial due to its impact on several aspects of our society,
such as disease spreading, urban planning, well-being, pollution, and more. The …
such as disease spreading, urban planning, well-being, pollution, and more. The …
Cross-domain weakly-supervised object detection through progressive domain adaptation
Can we detect common objects in a variety of image domains without instance-level
annotations? In this paper, we present a framework for a novel task, cross-domain weakly …
annotations? In this paper, we present a framework for a novel task, cross-domain weakly …
GETNext: trajectory flow map enhanced transformer for next POI recommendation
Next POI recommendation intends to forecast users' immediate future movements given their
current status and historical information, yielding great values for both users and service …
current status and historical information, yielding great values for both users and service …
Revisiting user mobility and social relationships in lbsns: a hypergraph embedding approach
Location Based Social Networks (LBSNs) have been widely used as a primary data source
to study the impact of mobility and social relationships on each other. Traditional …
to study the impact of mobility and social relationships on each other. Traditional …
Interaction-enhanced and time-aware graph convolutional network for successive point-of-interest recommendation in traveling enterprises
Extensive user check-in data incorporating user preferences for location is collected through
Internet of Things (IoT) devices, including cell phones and other sensing devices in location …
Internet of Things (IoT) devices, including cell phones and other sensing devices in location …
Graph neural networks in IoT: A survey
The Internet of Things (IoT) boom has revolutionized almost every corner of people's daily
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …
lives: healthcare, environment, transportation, manufacturing, supply chain, and so on. With …
Personalized long-and short-term preference learning for next POI recommendation
Next POI recommendation has been studied extensively in recent years. The goal is to
recommend next POI for users at specific time given users' historical check-in data …
recommend next POI for users at specific time given users' historical check-in data …
Privacy-aware point-of-interest category recommendation in internet of things
In location-based social networks (LBSNs), extensive user check-in data incorporating user
preferences for location is collected through Internet of Things devices, including cell …
preferences for location is collected through Internet of Things devices, including cell …
Personalized privacy-preserving task allocation for mobile crowdsensing
Location information of workers are usually required for optimal task allocation in mobile
crowdsensing, which however raises severe concerns of location privacy leakage. Although …
crowdsensing, which however raises severe concerns of location privacy leakage. Although …