Work

Regularization path via L0 Bregman relaxations

Year: 2025

Type: conference-paper

Abstract: National audience

Source: HAL (Le Centre pour la Communication Scientifique Directe)

Authors: Essafri, Mhamed, Calatroni, Luca, Soubies, Emmanuel

Institutions: Institut de Recherche en Informatique de Toulouse, University of Genoa

Language: English

Topic: Statistical Methods and Inference

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

Open Access status: green

Funders: Agence Nationale de la Recherche, HORIZON EUROPE European Research Council

Awards: Model-aware learning for imaging inverse problems in fluorescence microscopy, Exact RelaxatiOns for Sparse and low-rank optImizatiON

OpenAlex ID: W4416734262

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