12 papers
Phase Transition for Stochastic Block Model with more than Communities
Alexandra Carpentier, Christophe Giraud, Nicolas Verzelen
Predictions from statistical physics postulate that recovery of the communities in the Stochastic Block Model (SBM) with a fixed number of communities is possible in polynomial…
The Sampling Complexity of Condorcet Winner Identification in Dueling Bandits
El Mehdi Saad, Victor Thuot, Nicolas Verzelen
We study best-arm identification in stochastic dueling bandits under the sole assumption that a Condorcet winner exists, i.e., an arm that wins each noisy pairwise comparison with…
Low-degree Lower bounds for clustering in moderate dimension
Alexandra Carpentier, Nicolas Verzelen
We study the fundamental problem of clustering points into groups drawn from a mixture of isotropic Gaussians in . Specifically, we investigate the requisite…
Nonparametric Kernel Clustering with Bandit Feedback
Victor Thuot, Sebastian Vogt, Debarghya Ghoshdastidar +1
Clustering with bandit feedback refers to the problem of partitioning a set of items, where the clustering algorithm can sequentially query the items to receive noisy observations.…
Low-degree lower bounds via almost orthonormal bases
Alexandra Carpentier, Simone Maria Giancola, Christophe Giraud +1
Low-degree polynomials have emerged as a powerful paradigm for providing evidence of statistical-computational gaps across a variety of high-dimensional statistical models [Wein25]…
Statistical and computational challenges in ranking
Alexandra Carpentier, Nicolas Verzelen
We consider the problem of ranking experts according to their abilities, based on the correctness of their answers to questions. This is modeled by the so-called crowd-sour…