5 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…
The Risk Quadrangle in Optimization: An Overview with Recent Results and Extensions
Bogdan Grechuk, Anton Malandii, Terry Rockafellar +1
This paper revisits and extends the 2013 development by Rockafellar and Uryasev of the Risk Quadrangle (RQ) as a unified scheme for integrating risk management, optimization, and s…
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…
Primal-Dual Stability in Local Optimality
Matus Benko, R. Tyrrell Rockafellar
Much is known about when a locally optimal solution depends in a single-valued Lipschitz continuous way on the problem's parameters, including tilt perturbations. Much less is know…