2 citations · 2 across the 6 of their papers we have counts for
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Sharp optimal recovery in the two-component Gaussian Mixture Model
Mohamed Ndaoud
This paper studies the problem of clustering in the two-component Gaussian mixture model where the centers are separated by for some . We characterize the exact phase tra…
Interplay of minimax estimation and minimax support recovery under sparsity
Mohamed Ndaoud
In this paper, we study a new notion of scaled minimaxity for sparse estimation in high-dimensional linear regression model. We present more optimistic lower bounds than the one gi…
Harmonic analysis meets stationarity: A general framework for series expansions of special Gaussian processes
M. Ndaoud
In this paper, we present a new approach to derive series expansions for some Gaussian processes based on harmonic analysis of their covariance function. In particular, we propose…
Optimal variable selection and adaptive noisy Compressed Sensing
Mohamed Ndaoud, Alexandre B. Tsybakov
In the context of high-dimensional linear regression models, we propose an algorithm of exact support recovery in the setting of noisy compressed sensing where all entries of the d…
Adaptive robust estimation in sparse vector model
Laëtitia Comminges, Olivier Collier, Mohamed Ndaoud +1
For the sparse vector model, we consider estimation of the target vector, of its L2-norm and of the noise variance. We construct adaptive estimators and establish the optimal rates…