Zobrazeno 1 - 10
of 149
pro vyhledávání: '"Butucea, Cristina"'
We consider a general class of statistical experiments, in which an $n$-dimensional centered Gaussian random variable is observed and its covariance matrix is the parameter of interest. The covariance matrix is assumed to be well-approximable in a li
Externí odkaz:
http://arxiv.org/abs/2410.05751
Autor:
Bettache, Nayel, Butucea, Cristina
The two-sided matrix regression model $Y = A^*X B^* +E$ aims at predicting $Y$ by taking into account both linear links between column features of $X$, via the unknown matrix $B^*$, and also among the row features of $X$, via the matrix $A^*$. We pro
Externí odkaz:
http://arxiv.org/abs/2303.04694
We consider a model where a signal (discrete or continuous) is observed with an additive Gaussian noise process. The signal is issued from a linear combination of a finite but increasing number of translated features. The features are continuously pa
Externí odkaz:
http://arxiv.org/abs/2212.01169
In this paper we observe a set, possibly a continuum, of signals corrupted by noise. Each signal is a finite mixture of an unknown number of features belonging to a continuous dictionary. The continuous dictionary is parametrized by a real non-linear
Externí odkaz:
http://arxiv.org/abs/2210.16311
We consider a general non-linear model where the signal is a finite mixture of an unknown, possibly increasing, number of features issued from a continuous dictionary parameterized by a real nonlinear parameter. The signal is observed with Gaussian (
Externí odkaz:
http://arxiv.org/abs/2207.00171
In the pivotal variable selection problem, we derive the exact non-asymptotic minimax selector over the class of all $s$-sparse vectors, which is also the Bayes selector with respect to the uniform prior. While this optimal selector is, in general, n
Externí odkaz:
http://arxiv.org/abs/2112.15042
Autor:
Butucea, Cristina, Issartel, Yann
We study the problem of estimating non-linear functionals of discrete distributions in the context of local differential privacy. The initial data $x_1,\ldots,x_n \in [K]$ are supposed i.i.d. and distributed according to an unknown discrete distribut
Externí odkaz:
http://arxiv.org/abs/2107.03940
We address the problem of goodness-of-fit testing for H\"older continuous densities under local differential privacy constraints. We study minimax separation rates when only non-interactive privacy mechanisms are allowed to be used and when both non-
Externí odkaz:
http://arxiv.org/abs/2107.02439
We consider $n$ independent $p$-dimensional Gaussian vectors with covariance matrix having Toeplitz structure. We test that these vectors have independent components against a stationary distribution with sparse Toeplitz covariance matrix, and also s
Externí odkaz:
http://arxiv.org/abs/2102.06817
We address the problem of variable selection in a high-dimensional but sparse mean model, under the additional constraint that only privatised data are available for inference. The original data are vectors with independent entries having a symmetric
Externí odkaz:
http://arxiv.org/abs/2011.14881