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Deception in Linear-Quadratic Control
Yerin Kim, Haosheng Zhou, Alexander Benvenuti +2
Systems operating in adversarial environments may inadvertently leak sensitive information to adversaries. To address this challenge, we revisit the linear-quadratic control framew…
Generating Differentially Private Networks with a Modified Erdős-Rényi Model
Huaiyuan Rao, Calvin Hawkins, Alexander Benvenuti +1
Differential privacy has been used to privately calculate numerous network properties, but existing approaches often require the development of a new privacy mechanism for each pro…
Differentially Private Linear Programming: Reduced Sub-Optimality and Guaranteed Constraint Satisfaction
Alexander Benvenuti, Brendan Bialy, Miriam Dennis +1
Linear programming is a fundamental tool in a wide range of decision systems. However, without privacy protections, sharing the solution to a linear program may reveal information…
Guaranteed Feasibility in Differentially Private Linearly Constrained Convex Optimization
Alexander Benvenuti, Brendan Bialy, Miriam Dennis +1
Convex programming with linear constraints plays an important role in the operation of a number of everyday systems. However, absent any additional protections, revealing or acting…