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Exact Recovery for System Identification with More Corrupt Data than Clean Data
We highlight that the attack vectors are allowed to be correlated with each other in this work, whereas we make some assumptions about the times at which the attacks happen.
Learning of Dynamical Systems under Adversarial Attacks -- Null Space Property Perspective
We study the identification of a linear time-invariant dynamical system affected by large-and-sparse disturbances modeling adversarial attacks or faults.
Semidefinite Programming versus Burer-Monteiro Factorization for Matrix Sensing
In this paper, we shed light on some major differences between these two methods.
Factorization Approach for Low-complexity Matrix Completion Problems: Exponential Number of Spurious Solutions and Failure of Gradient Methods
It is well-known that the Burer-Monteiro (B-M) factorization approach can efficiently solve low-rank matrix optimization problems under the RIP condition.
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