Graph Neural Network (GNN) training and inference involve significant
ch...
Graph Convolutional Networks (GCNs) are extensively utilized for deep
le...
While machine learning and ranking-based systems are in widespread use f...
Synthetic data generation is a fundamental task for many data management...
Current approaches for modeling propagation in networks (e.g., spread of...
Shortest path queries over graphs are usually considered as isolated tas...
Sharing sensitive data is vital in enabling many modern data analysis an...
Sharing trajectories is beneficial for many real-world applications, suc...
The state-of-the-art deep neural networks (DNNs) have significant
comput...
We present PPQ-trajectory, a spatio-temporal quantization based solution...
We present a scalable solution to link entities across mobility datasets...
The social media explosion has populated the Internet with a wealth of
i...
Analysis of word embedding properties to inform their use in downstream ...
Faster and more cost-efficient, crowdsourced delivery is needed to meet ...
We are witnessing an enormous growth in the volume of data generated by
...
Today, vast amounts of location data are collected by various service
pr...