3 citations · 4 across the 7 of their papers we have counts for
8 papers
Goodness-of-Fit Testing for Groupwise Spherical Error Structures
Daria Tieplova, Nina Dörnemann, Tim Kutta
The analysis of large data panels is important in econometrics and beyond. Prediction and inference methods for such data typically rely on simplifying model assumptions for the co…
Change Point Detection and Localization in High-Dimensional Time Series
Patrick Bastian, Daria Tieplova, Nina Dörnemann +1
We present new inference tools for change point detection in high-dimensional time series. We discuss two distinct statistical applications: First, sequential change point testing…
Information-theoretic reduction of deep neural networks to linear models in the overparametrized proportional regime
Francesco Camilli, Daria Tieplova, Eleonora Bergamin +1
We rigorously analyse fully-trained neural networks of arbitrary depth in the Bayesian optimal setting in the so-called proportional scaling regime where the number of training sam…
Information-theoretic limits and approximate message-passing for high-dimensional time series
Daria Tieplova, Samriddha Lahiry, Jean Barbier
High-dimensional time series appear in many scientific setups, demanding a nuanced approach to model and analyze the underlying dependence structure. Theoretical advancements so fa…
Fundamental limits of overparametrized shallow neural networks for supervised learning
Francesco Camilli, Daria Tieplova, Jean Barbier
We carry out an information-theoretical analysis of a two-layer neural network trained from input-output pairs generated by a teacher network with matching architecture, in overpar…
On the largest singular values of certain large random matrices with application to the estimation of the minimal dimension of the state-space representations of high-dimensional time series
Daria Tieplova, Philippe Loubaton
This paper is devoted to the estimation of the minimal dimension P of the state-space realizations of a high-dimensional time series y, defined as a noisy version (the noise is whi…
On the behaviour of large empirical autocovariance matrices between the past and the future
Philippe Loubaton, Daria Tieplova
The asymptotic behaviour of the distribution of the squared singular values of the sample autocovariance matrix between the past and the future of a high-dimensional complex Gaussi…
Distribution of eigenvalues of sample covariance matrices with tensor product samples
Daria Tieplova
We consider real symmetric and hermitian matrices , which are equal to sum of tensor products of vectors , , where…