8 citations · 10 across the 12 of their papers we have counts for
6 papers · 1 filter
Network-Constrained Policy Optimization for Adaptive Multi-agent Vehicle Routing
Fazel Arasteh, Arian Haghparast, Manos Papagelis
Traffic congestion in urban road networks leads to longer trip times and higher emissions, especially during peak periods. While the Shortest Path First (SPF) algorithm is optimal…
TraceHiding: Scalable Machine Unlearning for Mobility Data
Ali Faraji, Manos Papagelis
This work introduces TraceHiding, a scalable, importance-aware machine unlearning framework for mobility trajectory data. Motivated by privacy regulations such as GDPR and CCPA gra…
GCN-TULHOR: Trajectory-User Linking Leveraging GCNs and Higher-Order Spatial Representations
Khoa Tran, Pranav Gupta, Manos Papagelis
Trajectory-user linking (TUL) aims to associate anonymized trajectories with the users who generated them, which is crucial for personalized recommendations, privacy-preserving ana…
TrajLearn: Trajectory Prediction Learning using Deep Generative Models
Amirhossein Nadiri, Jing Li, Ali Faraji +2
Trajectory prediction aims to estimate an entity's future path using its current position and historical movement data, benefiting fields like autonomous navigation, robotics, and…
PathletRL++: Optimizing Trajectory Pathlet Extraction and Dictionary Formation via Reinforcement Learning
Gian Alix, Arian Haghparast, Manos Papagelis
Advances in tracking technologies have spurred the rapid growth of large-scale trajectory data. Building a compact collection of pathlets, referred to as a trajectory pathlet dicti…
Elastic Bulk Synchronous Parallel Model for Distributed Deep Learning
Xing Zhao, Manos Papagelis, Aijun An +3
The bulk synchronous parallel (BSP) is a celebrated synchronization model for general-purpose parallel computing that has successfully been employed for distributed training of mac…