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Graph Matching via convex relaxation to the simplex
We use this condition to show exact one-step recovery of the ground truth (holding almost surely) via the mirror descent scheme, in the noiseless setting.
Random Geometric Graphs on Euclidean Balls
We construct an estimator for the latent norms based on the degree of the nodes of an observed graph in the case of the model where the edge probability is given by $f(\langle X_i, X_j\rangle)=\mathbbm{1}_{\langle X_i, X_j\rangle\geq \tau}$, where $0<\tau<1$.
Relative concentration bounds for the spectrum of kernel matrices
The inequalities presented here are of relative type, meaning that they scale with the eigenvalue in consideration, which results in convergence rates that vary across the spectrum.
