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20042026
most citedFurther Remarks on Strict Input-to-State Stable Lyapunov Functions for Time-Varying Systems

63 citations

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15 papers · 1 filter

math.ST2025

Computational barriers for permutation-based problems, and cumulants of weakly dependent random variables

Bertrand Even, Christophe Giraud, Nicolas Verzelen

In many high-dimensional problems,polynomial-time algorithms fall short of achieving the statistical limits attainable without computational constraints. A powerful approach to pro…

math.ST2024

Seriation of Toeplitz and latent position matrices: optimal rates and computational trade-offs

Clément Berenfeld, Alexandra Carpentier, Nicolas Verzelen

In this paper, we consider the problem of seriation of a permuted structured matrix based on noisy observations. The entries of the matrix relate to an expected quantification of i…

math.ST2024

Computation-information gap in high-dimensional clustering

Bertrand Even, Christophe Giraud, Nicolas Verzelen

We investigate the existence of a fundamental computation-information gap for the problem of clustering a mixture of isotropic Gaussian in the high-dimensional regime, where the am…

math.ST2023

Optimal rates for ranking a permuted isotonic matrix in polynomial time

Emmanuel Pilliat, Alexandra Carpentier, Nicolas Verzelen

We consider a ranking problem where we have noisy observations from a matrix with isotonic columns whose rows have been permuted by some permutation *. This encompasses many mo…

math.ST2019★ 3 cited

Detecting a planted community in an inhomogeneous random graph

Kay Bogerd, Rui M. Castro, Remco van der Hofstad +1

We study the problem of detecting whether an inhomogeneous random graph contains a planted community. Specifically, we observe a single realization of a graph. Under the null hypot…

math.ST2018★ 1 cited

Partial recovery bounds for clustering with the relaxed means

Christophe Giraud, Nicolas Verzelen

We investigate the clustering performances of the relaxed means in the setting of sub-Gaussian Mixture Model (sGMM) and Stochastic Block Model (SBM). After identifying the appro…