4 papers
On the privacy cost for dependent Gaussian data: spectral density estimation under local differential privacy
Yann Issartel, François Roueff
We study the fundamental problem of estimating the dependence structure of a centered stationary Gaussian process under local differential privacy (LDP). In this setting, the spect…
Active Seriation: Efficient Ordering Recovery with Statistical Guarantees
James Cheshire, Yann Issartel
Active seriation aims at recovering an unknown ordering of items by adaptively querying pairwise similarities. The observations are noisy measurements of entries of an underlyi…
Minimax optimal seriation in polynomial time
Yann Issartel, Christophe Giraud, Nicolas Verzelen
We consider the seriation problem, whose goal is to recover a hidden ordering from a noisy observation of a permuted Robinson matrix. We establish sharp minimax rates under average…
On the Estimation of Network Complexity: Dimension of Graphons
Yann Issartel
Network complexity has been studied for over half a century and has found a wide range of applications. Many methods have been developed to characterize and estimate the complexity…