2 citations · 2 across the 7 of their papers we have counts for
7 papers
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…
Exact Recovery Guarantees for Parameterized Nonlinear System Identification Problem under Sparse Disturbances or Semi-Oblivious Attacks
Haixiang Zhang, Baturalp Yalcin, Javad Lavaei +1
In this work, we study the problem of learning a nonlinear dynamical system by parameterizing its dynamics using basis functions. We assume that disturbances occur at each time ste…
Exact Recovery for System Identification with More Corrupt Data than Clean Data
Baturalp Yalcin, Haixiang Zhang, Javad Lavaei +1
This paper investigates the system identification problem for linear discrete-time systems under adversaries and analyzes two lasso-type estimators. We examine both asymptotic and…
Learning of Dynamical Systems under Adversarial Attacks -- Null Space Property Perspective
Han Feng, Baturalp Yalcin, Javad Lavaei
We study the identification of a linear time-invariant dynamical system affected by large-and-sparse disturbances modeling adversarial attacks or faults. Under the assumption that…
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing
Baturalp Yalcin, Ziye Ma, Javad Lavaei +1
Many fundamental low-rank optimization problems, such as matrix completion, phase synchronization/retrieval, power system state estimation, and robust PCA, can be formulated as the…
A New Complexity Metric for Nonconvex Rank-one Generalized Matrix Completion
Haixiang Zhang, Baturalp Yalcin, Javad Lavaei +1
In this work, we develop a new complexity metric for an important class of low-rank matrix optimization problems in both symmetric and asymmetric cases, where the metric aims to qu…
Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods
Baturalp Yalcin, Haixiang Zhang, Javad Lavaei +1
It is well-known that the Burer-Monteiro (B-M) factorization approach can efficiently solve low-rank matrix optimization problems under the RIP condition. It is natural to ask whet…