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Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Sélection de caractéristique

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Using Cardio-Respiratory Signals to Recognize Emotions Elicited by Watching Music Video Clips

Isotropic Resolution in Fluorescence Imaging by Single Particle Reconstruction

Incremental Consistency Guarantees for Replicated Objects

Automatic and computationally efficient method for model selection in inertial sensor calibration

A simple model-based approach to variable selection in classification and clustering

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid-infrared spectroscopy

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Transfer Learning through Greedy Subset Selection

Multitask diffusion LMS with sparsity-based regularization

Learning Separable Filters

Automatic and computationally efficient method for model selection in inertial sensor calibration

Multitask diffusion LMS with sparsity-based regularization

Model selection for partial least squares calibration and implications for analysis of atmospheric organic aerosol samples with mid-infrared spectroscopy

Isotropic Resolution in Fluorescence Imaging by Single Particle Reconstruction

Incremental Consistency Guarantees for Replicated Objects

A simple model-based approach to variable selection in classification and clustering

Transfer Learning through Greedy Subset Selection

Using Cardio-Respiratory Signals to Recognize Emotions Elicited by Watching Music Video Clips

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Learning Separable Filters