Outliers in the spectrum of iid matrices with bounded rank perturbations

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Linking Connectivity, Dynamics, and Computations in Low-Rank Recurrent Neural Networks. (2017, unknown): “We can then apply results from random matrix theory (Tao, 2013) which predict that, in the large N limit, the eigenspectra of the random and the structured parts do not interact, but sum together.”
Spectrum of Markov Generators on Sparse Random Graphs (2012, methodology): “We will rely on a method that has already been successfully used in random matrix models with finite rank perturbations, for example in [5, 40].”
Around the circular law (2011, background): “Yet another model related to projections in which each row has a zero sum is studied in [142].”
Outlier Eigenvalues for Deformed I.I.D. Random Matrices (2014, background): “It generalizes Tao [51, Theorem 1.7] where A′N = 0.”