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Hong Phuong Dang
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2020 – today
- 2023
- [i2]Thu-Le Tran, Clément Elvira, Hong Phuong Dang, Cédric Herzet:
One to beat them all: "RYU" - a unifying framework for the construction of safe balls. CoRR abs/2312.00640 (2023) - 2022
- [c6]Thu-Le Tran, Clément Elvira, Hong Phuong Dang, Cédric Herzet:
Beyond GAP screening for Lasso by exploiting new dual cutting half-spaces. EUSIPCO 2022: 2056-2060 - [c5]Cédric Herzet, Clément Elvira, Hong Phuong Dang:
Region-free Safe Screening Tests for $\ell_{1}$-penalized Convex Problems. EUSIPCO 2022: 2061-2065 - [i1]Thu-Le Tran, Clément Elvira, Hong Phuong Dang, Cédric Herzet:
Beyond GAP screening for Lasso by exploiting new dual cutting half-spaces with supplementary material. CoRR abs/2203.00987 (2022) - 2021
- [j3]Hong Phuong Dang, Myriam Vimond, Ségolen Geffray:
Data-Driven Parameter Choice for Illumination Artifact Correction of Digital Images. IEEE Signal Process. Lett. 28: 155-159 (2021)
2010 – 2019
- 2019
- [c4]Hong Phuong Dang, Clément Elvira:
Parameter-free Small Variance Asymptotics for Dictionary Learning. EUSIPCO 2019: 1-5 - 2018
- [j2]Hong Phuong Dang, Pierre Chainais:
Towards Dictionaries of Optimal Size: A Bayesian Non Parametric Approach. J. Signal Process. Syst. 90(2): 221-232 (2018) - [c3]Clement Elvira, Hong Phuong Dang, Pierre Chainais:
Small variance asymptotics and bayesian nonparametrics for dictionary learning. EUSIPCO 2018: 1607-1611 - 2017
- [j1]Hong Phuong Dang, Pierre Chainais:
Indian Buffet Process dictionary learning: Algorithms and applications to image processing. Int. J. Approx. Reason. 83: 1-20 (2017) - 2016
- [b1]Hong Phuong Dang:
Approches bayésiennes non paramétriques et apprentissage de dictionnaire pour les problèmes inverses en traitement d'image. (Bayesian nonparametric approaches and dictionary learning for inverse problems in image processing). École centrale de Lille, France, 2016 - [c2]Hong Phuong Dang, Pierre Chainais:
Indian Buffet process dictionary learning for image inpainting. SSP 2016: 1-5 - 2015
- [c1]Hong Phuong Dang, Pierre Chainais:
A Bayesian non parametric approach to learn dictionaries with adapted numbers of atoms. MLSP 2015: 1-6
Coauthor Index
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