26 citations · 56 across the 9 of their papers we have counts for
10 papers
Convergence and Margin of Adversarial Training on Separable Data
Zachary Charles, Shashank Rajput, Stephen Wright +1
Adversarial training is a technique for training robust machine learning models. To encourage robustness, it iteratively computes adversarial examples for the model, and then re-tr…
Training Set Debugging Using Trusted Items
Xuezhou Zhang, Xiaojin Zhu, Stephen J. Wright
Training set bugs are flaws in the data that adversely affect machine learning. The training set is usually too large for man- ual inspection, but one may have the resources to ver…
Complexity analysis of second-order line-search algorithms for smooth nonconvex optimization
Clément W. Royer, Stephen J. Wright
There has been much recent interest in finding unconstrained local minima of smooth functions, due in part of the prevalence of such problems in machine learning and robust statist…
Vulnerability Analysis of Power Systems
Taedong Kim, Stephen J. Wright, Daniel Bienstock +1
Potential vulnerabilities in a power grid can be exposed by identifying those transmission lines on which attacks (in the form of interference with their transmission capabilities)…
Coordinate Descent Algorithms
Stephen J. Wright
Coordinate descent algorithms solve optimization problems by successively performing approximate minimization along coordinate directions or coordinate hyperplanes. They have been…
PMU Placement for Line Outage Identification via Multiclass Logistic Regression
Taedong Kim, Stephen J. Wright
We consider the problem of identifying a single line outage in a power grid by using data from phasor measurement units (PMUs). When a line outage occurs, the voltage phasor of eac…