no code implementations • 6 Aug 2021 • Christophe Giraud, Yann Issartel, Nicolas Verzelen
We consider the problem of estimating latent positions in a one-dimensional torus from pairwise affinities.
no code implementations • NeurIPS 2021 • Cristina Butucea, Yann Issartel
In the non-interactive case, we study two plug-in type estimators of $F_{\gamma}$, for all $\gamma >0$, that are similar to the MLE analyzed by Jiao et al. (2017) in the multinomial model.
no code implementations • NeurIPS 2021 • Cristina Butucea, Yann Issartel
In the non-interactive case, we study several plug-in type estimators of $F_{\gamma}$, for all $\gamma >0$, that are similar to the MLE which has been analyzed by Jiao et al. (2017) in the multinomial model.
no code implementations • 6 Sep 2019 • Yann Issartel
Based on this estimated distance, we compute the corresponding covering number and Minkowski dimension and we provide optimal non-asymptotic error bounds for these two plug-in estimators.
no code implementations • 17 May 2019 • Christophe Giraud, Yann Issartel, Luc Lehéricy, Matthieu Lerasle
This paper shows that sublinear regret is achievable in the case where the graph is generated according to a Stochastic Block Model (SBM) with two communities.