57 citations · 200 across the 66 of their papers we have counts for
7 papers · 1 filter
Efficient Learning of Distributed Linear-Quadratic Controllers
Salar Fattahi, Nikolai Matni, Somayeh Sojoudi
In this work, we propose a robust approach to design distributed controllers for unknown-but-sparse linear and time-invariant systems. By leveraging modern techniques in distribute…
Boundary Defense against Cyber Threat for Power System Operation
Ming Jin, Javad Lavaei, Somayeh Sojoudi +1
The operation of power grids is becoming increasingly data-centric. While the abundance of data could improve the efficiency of the system, it poses major reliability challenges. I…
Global Optimality Guarantees for Nonconvex Unsupervised Video Segmentation
Brendon G. Anderson, Somayeh Sojoudi
In this paper, we consider the problem of unsupervised video object segmentation via background subtraction. Specifically, we pose the nonsemantic extraction of a video's moving ob…
Power up! Robust Graph Convolutional Network via Graph Powering
Ming Jin, Heng Chang, Wenwu Zhu +1
Graph convolutional networks (GCNs) are powerful tools for graph-structured data. However, they have been recently shown to be vulnerable to topological attacks. To enhance adversa…
On the Absence of Spurious Local Trajectories in Time-varying Nonconvex Optimization
S. Fattahi, C. Josz, Y. Ding +3
In this paper, we study the landscape of an online nonconvex optimization problem, for which the input data vary over time and the solution is a trajectory rather than a single poi…
Learning Sparse Dynamical Systems from a Single Sample Trajectory
Salar Fattahi, Nikolai Matni, Somayeh Sojoudi
This paper addresses the problem of identifying sparse linear time-invariant (LTI) systems from a single sample trajectory generated by the system dynamics. We introduce a Lasso-li…
Sharp Restricted Isometry Bounds for the Inexistence of Spurious Local Minima in Nonconvex Matrix Recovery
Richard Y. Zhang, Somayeh Sojoudi, Javad Lavaei
Nonconvex matrix recovery is known to contain no spurious local minima under a restricted isometry property (RIP) with a sufficiently small RIP constant . If is too large, h…