26 citations · 58 across the 8 of their papers we have counts for
4 papers · 1 filter
Anderson acceleration of coordinate descent
Quentin Bertrand, Mathurin Massias
Acceleration of first order methods is mainly obtained via inertial techniques à la Nesterov, or via nonlinear extrapolation. The latter has known a recent surge of interest, with…
Model identification and local linear convergence of coordinate descent
Quentin Klopfenstein, Quentin Bertrand, Alexandre Gramfort +2
For composite nonsmooth optimization problems, Forward-Backward algorithm achieves model identification (e.g. support identification for the Lasso) after a finite number of iterati…
Implicit differentiation of Lasso-type models for hyperparameter optimization
Quentin Bertrand, Quentin Klopfenstein, Mathieu Blondel +3
Setting regularization parameters for Lasso-type estimators is notoriously difficult, though crucial in practice. The most popular hyperparameter optimization approach is grid-sear…
Support recovery and sup-norm convergence rates for sparse pivotal estimation
Mathurin Massias, Quentin Bertrand, Alexandre Gramfort +1
In high dimensional sparse regression, pivotal estimators are estimators for which the optimal regularization parameter is independent of the noise level. The canonical pivotal est…