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11/26/2022
Synergies Between Disentanglement and Sparsity: a Multi-Task Learning Perspective
Although disentangled representations are often said to be beneficial fo...
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09/27/2022
The Curse of Unrolling: Rate of Differentiating Through Optimization
Computing the Jacobian of the solution of an optimization problem is a c...
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06/21/2022
On the Limitations of Elo: Real-World Games, are Transitive, not Additive
Real-world competitive games, such as chess, go, or StarCraft II, rely o...
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04/16/2022
Beyond L1: Faster and Better Sparse Models with skglm
We propose a new fast algorithm to estimate any sparse generalized linea...
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05/04/2021
Implicit differentiation for fast hyperparameter selection in non-smooth convex learning
Finding the optimal hyperparameters of a model can be cast as a bilevel ...
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11/19/2020
Anderson acceleration of coordinate descent
Acceleration of first order methods is mainly obtained via inertial tech...
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10/22/2020
Model identification and local linear convergence of coordinate descent
For composite nonsmooth optimization problems, Forward-Backward algorith...
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02/20/2020
Implicit differentiation of Lasso-type models for hyperparameter optimization
Setting regularization parameters for Lasso-type estimators is notorious...
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01/15/2020
Support recovery and sup-norm convergence rates for sparse pivotal estimation
In high dimensional sparse regression, pivotal estimators are estimators...
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02/07/2019
Concomitant Lasso with Repetitions (CLaR): beyond averaging multiple realizations of heteroscedastic noise
Sparsity promoting norms are frequently used in high dimensional regress...
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07/27/2017