9 papers · 1 filter
Huber-based Robust System Identification with Near-Optimal Guarantees Across Independent and Adversarial Regimes
Jihun Kim, Javad Lavaei
Dynamical systems can confront one of two extreme types of disturbances: persistent zero-mean independent noise, and sparse nonzero-mean adversarial attacks, depending on the speci…
A Trust-Region Interior-Point Stochastic Sequential Quadratic Programming Method
Yuchen Fang, Jihun Kim, Sen Na +2
In this paper, we propose a trust-region interior-point stochastic sequential quadratic programming (TR-IP-SSQP) method for solving optimization problems with a stochastic objectiv…
TRSVR: An Adaptive Stochastic Trust-Region Method with Variance Reduction
Yuchen Fang, Xinshou Zheng, Javad Lavaei
We propose a stochastic trust-region method for unconstrained nonconvex optimization that incorporates stochastic variance-reduced gradients (SVRG) to accelerate convergence. Unlik…
Bridging Batch and Streaming Estimations to System Identification under Adversarial Attacks
Jihun Kim, Javad Lavaei
System identification in modern engineering systems faces emerging challenges from unanticipated adversarial attacks beyond existing detection mechanisms. In this work, we obtain a…
System Identification from Partial Observations under Adversarial Attacks
Jihun Kim, Javad Lavaei
This paper is concerned with the partially observed linear system identification, where the goal is to obtain reasonably accurate estimation of the balanced truncation of the true…
Subgradient Method for System Identification with Non-Smooth Objectives
Baturalp Yalcin, Jihun Kim, Javad Lavaei
This paper investigates a subgradient-based algorithm to solve the system identification problem for linear time-invariant systems with non-smooth objectives. This is essential for…