9 papers
MPE: A Mobility Pattern Embedding Model for Predicting Next Locations
Meng Chen, Xiaohui Yu, Yang Liu
The wide spread use of positioning and photographing devices gives rise to a deluge of traffic trajectory data (e.g., vehicle passage records and taxi trajectory data), with each r…
NLPMM: a Next Location Predictor with Markov Modeling
Meng Chen, Yang Liu, Xiaohui Yu
In this paper, we solve the problem of predicting the next locations of the moving objects with a historical dataset of trajectories. We present a Next Location Predictor with Mark…
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms
Qianyu Guo, Sen Chen, Xiaofei Xie +6
Deep Learning (DL) has recently achieved tremendous success. A variety of DL frameworks and platforms play a key role to catalyze such progress. However, the differences in archite…
Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks
Yaqin Zhou, Shangqing Liu, Jingkai Siow +2
Vulnerability identification is crucial to protect the software systems from attacks for cyber security. It is especially important to localize the vulnerable functions among the s…
Federated Forest
Yang Liu, Yingting Liu, Zhijie Liu +3
Most real-world data are scattered across different companies or government organizations, and cannot be easily integrated under data privacy and related regulations such as the Eu…
Collider phenomenology of a unified leptoquark model
Thomas Faber, Matěj Hudec, Helena Kolešová +4
We demonstrate that in a recently proposed unified leptoquark model based on the gauge group significant deviations from the Standard Model va…