3 citations · 3 across the 7 of their papers we have counts for
7 papers
Constraint-Aware Influence Estimation in Deep Constrained Learning
Xin Wang, R. Tyrrell Rockafellar, Xuegang +1
Constrained learning has been increasingly applied to various domains to ensure explicit feasibility requirements due to fairness, safety, robustness, regularization, and physics o…
Secure and Efficient -Norm Computation for Two-Party Learning Applications
Ali Arastehfard, Weiran Liu, Joshua Lee +3
Secure norm computation is becoming increasingly important in many real-world learning applications. However, existing cryptographic systems often lack a general framework for secu…
SecureV2X: An Efficient and Privacy-Preserving System for Vehicle-to-Everything (V2X) Applications
Joshua Lee, Ali Arastehfard, Weiran Liu +2
Autonomous driving and V2X technologies have developed rapidly in the past decade, leading to improved safety and efficiency in modern transportation. These systems interact with e…
Machine Unlearning of Traffic State Estimation and Prediction
Xin Wang, R. Tyrrell Rockafellar, Xuegang +1
Data-driven traffic state estimation and prediction (TSEP) relies heavily on data sources that contain sensitive information. While the abundance of data has fueled significant bre…
Model-Targeted Data Poisoning Attacks against ITS Applications with Provable Convergence
Xin Wang, Feilong Wang, Yuan Hong +3
The growing reliance of intelligent systems on data makes the systems vulnerable to data poisoning attacks. Such attacks could compromise machine learning or deep learning models b…
Set-Valued Sensitivity Analysis of Deep Neural Networks
Xin Wang, Feilong Wang, Xuegang Ban
This paper proposes a sensitivity analysis framework based on set valued mapping for deep neural networks (DNN) to understand and compute how the solutions (model weights) of DNN r…
Mitigating biases in big mobility data: a case study of monitoring large-scale transit systems
Feilong Wang, Xuegang Ban, Peng Chen +2
Big mobility datasets (BMD) have shown many advantages in studying human mobility and evaluating the performance of transportation systems. However, the quality of BMD remains poor…