Yapa: Accelerated Proximal Algorithm for Convex Composite Problems

Autor: Giovanni Chierchia, Mireille El Gheche

Publikováno v: ICASSP
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Jun 2021, Toronto, France. pp.5534-5538, ⟨10.1109/ICASSP39728.2021.9414656⟩

Proximal splitting methods are standard tools for nonsmooth optimization. While primal-dual methods have become very popular in the last decade for their flexibility, primal methods may still be preferred for two reasons: acceleration schemes are mor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c3bca23ac73d5c036f8c8b62ecc22e53
https://doi.org/10.1109/icassp39728.2021.9414656

Forward-Backward Splitting for Optimal Transport Based Problems

Autor: Guillermo Ortiz-Jimenez, Hermina Petric Maretic, Mireille El Gheche, Pascal Frossard, Effrosyni Simou

Publikováno v: ICASSP

Optimal transport aims to estimate a transportation plan that minimizes a displacement cost. This is realized by optimizing the scalar product between the sought plan and the given cost, over the space of doubly stochastic matrices. When the entropy

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6c351b612b6b88c17abffc2ea49d94e
https://doi.org/10.1109/icassp40776.2020.9053335

OrthoNet: Multilayer Network Data Clustering

Autor: Pascal Frossard, Mireille El Gheche, Giovanni Chierchia

Publikováno v: IEEE Transactions on Signal and Information Processing over Networks
IEEE Transactions on Signal and Information Processing over Networks, IEEE, 2020, 6, pp.152-162. ⟨10.1109/TSIPN.2020.2970313⟩
IEEE transactions on Signal and Information Processing over Networks
IEEE transactions on Signal and Information Processing over Networks, IEEE, 2020, 6, pp.152-162. ⟨10.1109/TSIPN.2020.2970313⟩

Network data appears in very diverse applications, like biological, social, or sensor networks. Clustering of network nodes into categories or communities has thus become a very common task in machine learning and data mining. Network data comes with

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::321d90fd8dff85c470df865167c03640
https://hal.archives-ouvertes.fr/hal-03131027

Robust and adaptive approaches for Relative Geologic Time Estimation

Autor: Marc Donias, Mireille El Gheche, Sebastien Guillon, Yannick Berthoumieu, Moctar Mounirou Arouna

Publikováno v: Journal of Applied Geophysics
Journal of Applied Geophysics, Elsevier, 2018, 159, pp.157-172. ⟨10.1016/j.jappgeo.2018.07.013⟩

For a geoscientist, the Relative Geologic Time (RGT) is an important tool to perform chronostratigraphic analysis. However, automatically estimate an RGT image from a seismic image can be a challenging task where we have to respect seismic features,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d973befd73e9529000d62fe7edb16ab9
https://hal.archives-ouvertes.fr/hal-02509426

Multitemporal SAR Image Despeckling Based on Block-Matching and Collaborative Filtering

Autor: Luisa Verdoliva, Mireille El Gheche, Giovanni Chierchia, Giuseppe Scarpa

Publikováno v: IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing, 2017, 55 (10), pp.5467-5480. ⟨10.1109/TGRS.2017.2707806⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2017, 55 (10), pp.5467-5480. ⟨10.1109/TGRS.2017.2707806⟩

International audience; We propose a despeckling algorithm for multitemporal synthetic aperture radar (SAR) images based on the concepts of block-matching and collaborative filtering. It relies on the nonlocal approach, and it is the extension of SAR

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c961343612d2d66b4ac2780ab8714429
https://hal.archives-ouvertes.fr/hal-01710027