no code implementations • NeurIPS 2020 • Jerome-Alexis Chevalier, Joseph Salmon, Alexandre Gramfort, Bertrand Thirion
To deal with this, we adapt the desparsified Lasso estimator ---an estimator tailored for high dimensional linear model that asymptotically follows a Gaussian distribution under sparsity and moderate feature correlation assumptions--- to temporal data corrupted with autocorrelated noise.