activity
20222025
most citedWasserstein Distributionally Robust Regret-Optimal Control in the Infinite-Horizon

2 citations · 4 across the 11 of their papers we have counts for

collaborators
Showing eess.SYShow all

7 papers · 1 filter

eess.SY2025

Beyond Quadratic Costs: A Bregman Divergence Approach to H Control

Joudi Hajar, Reza Ghane, Babak Hassibi

In the past couple of decades, non-quadratic convex penalties have reshaped signal processing and machine learning; in robust control, however, general convex costs break the Ricca…

eess.SY2025

Beyond Quadratic Costs in LQR: Bregman Divergence Control

Babak Hassibi, Joudi Hajar, Reza Ghane

In the past couple of decades, the use of ``non-quadratic" convex cost functions has revolutionized signal processing, machine learning, and statistics, allowing one to customize s…

eess.SY2024

Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach

Hiroyasu Tsukamoto, Joudi Hajar, Soon-Jo Chung +1

Modern control designs in robotics, aerospace, and cyber-physical systems rely heavily on real-world data obtained through system outputs. However, these outputs can be compromised…

eess.SY2024★ 1 cited

Robust Optimal Network Topology Switching for Zero Dynamics Attacks

Hiroyasu Tsukamoto, Joshua D. Ibrahim, Joudi Hajar +3

The intrinsic, sampling, and enforced zero dynamics attacks (ZDAs) are among the most detrimental stealthy attacks in robotics, aerospace, and cyber-physical systems. They exploit…

eess.SY2023★ 2 cited

Wasserstein Distributionally Robust Regret-Optimal Control in the Infinite-Horizon

Taylan Kargin, Joudi Hajar, Vikrant Malik +1

We investigate the Distributionally Robust Regret-Optimal (DR-RO) control of discrete-time linear dynamical systems with quadratic cost over an infinite horizon. Regret is the diff…

eess.SY2023

Regret-Optimal Control under Partial Observability

Joudi Hajar, Oron Sabag, Babak Hassibi

This paper studies online solutions for regret-optimal control in partially observable systems over an infinite-horizon. Regret-optimal control aims to minimize the difference in L…