39 citations · 157 across the 35 of their papers we have counts for
5 papers · 1 filter
SAIF: Sparse Adversarial and Imperceptible Attack Framework
Tooba Imtiaz, Morgan Kohler, Jared Miller +5
Adversarial attacks hamper the decision-making ability of neural networks by perturbing the input signal. The addition of calculated small distortion to images, for instance, can d…
Superstabilizing Control of Discrete-Time ARX Models under Error in Variables
Jared Miller, Tianyu Dai, Mario Sznaier
This paper applies a polynomial optimization based framework towards the superstabilizing control of an Autoregressive with Exogenous Input (ARX) model given noisy data observation…
Data-Driven Stabilizing and Robust Control of Discrete-Time Linear Systems with Error in Variables
Jared Miller, Tianyu Dai, Mario Sznaier
This work presents a sum-of-squares (SOS) based framework to perform data-driven stabilization and robust control tasks on discrete-time linear systems where the full-state observa…
Data-Driven Gain Scheduling Control of Linear Parameter-Varying Systems using Quadratic Matrix Inequalities
Jared Miller, Mario Sznaier
This paper synthesizes a gain-scheduled controller to stabilize all possible Linear Parameter-Varying (LPV) plants that are consistent with measured input/state data records. Inspi…
A Globally Convergent LP and SOCP-based algorithm for Semidefinite Programming
Biel Roig-Solvas, Mario Sznaier
Semidefinite programs (SDP) are one of the most versatile frameworks in numerical optimization, serving as generalizations of many conic programs and as relaxations of NP-hard comb…