4 papers
Statistical-computational gap in multiple Gaussian graph alignment
Bertrand Even, Luca Ganassali
We investigate the existence of a statistical-computational gap in multiple Gaussian graph alignment. We first generalize a previously established informational threshold from Vass…
Computational barriers for permutation-based problems, and cumulants of weakly dependent random variables
Bertrand Even, Christophe Giraud, Nicolas Verzelen
In many high-dimensional problems,polynomial-time algorithms fall short of achieving the statistical limits attainable without computational constraints. A powerful approach to pro…
Computational lower bounds in latent models: clustering, sparse-clustering, biclustering
Bertrand Even, Christophe Giraud, Nicolas Verzelen
In many high-dimensional problems, like sparse-PCA, planted clique, or clustering, the best known algorithms with polynomial time complexity fail to reach the statistical performan…
Computation-information gap in high-dimensional clustering
Bertrand Even, Christophe Giraud, Nicolas Verzelen
We investigate the existence of a fundamental computation-information gap for the problem of clustering a mixture of isotropic Gaussian in the high-dimensional regime, where the am…