Skip to Main content Skip to Navigation
  1. Search


...
inria-00137865v2  Reports
Jean-Daniel Boissonnat, Frank Nielsen, Richard Nock. Bregman Voronoi Diagrams: Properties, Algorithms and Applications
[Research Report] RR-6154, INRIA. 2007, pp.48
...
inria-00542337v1  Reports
Michèle Basseville. Divergence measures for statistical data processing
[Research Report] PI-1961, 2010, pp.23
hal-00712673v1  Conference papers
Meizhu Liu, Baba Vemuri, Rachid Deriche. UNSUPERVISED AUTOMATIC WHITE MATTER FIBER CLUSTERING USING A GAUSSIAN MIXTURE MODEL
IEEE International Symposium on Biomedical Imaging (ISBI)., May 2012, Barcelona, Spain. pp.522-525
hal-01973935v1  Journal articles
Rajendra Bhatia, Stéphane Gaubert, Tanvi Jain. Matrix versions of the Hellinger distance
Letters in Mathematical Physics, Springer Verlag, 2019, 109, pp.1777-1804. ⟨10.1007/s11005-019-01156-0⟩
...
hal-01673027v1  Preprints, Working Papers, ...
Alessandro Benfenati, Emilie Chouzenoux, Jean-Christophe Pesquet. A proximal approach for a class of matrix optimization problems
2017
...
hal-01096124v1  Journal articles
Jean-David Benamou, Guillaume Carlier, Marco Cuturi, Luca Nenna, Gabriel Peyré. Iterative Bregman Projections for Regularized Transportation Problems
SIAM Journal on Scientific Computing, Society for Industrial and Applied Mathematics, 2015, 2 (37), pp.A1111-A1138. ⟨10.1137/141000439⟩
...
hal-00488441v1  Journal articles
Jean-Daniel Boissonnat, Frank Nielsen, Richard Nock. Bregman Voronoi diagrams
Discrete and Computational Geometry, Springer Verlag, 2010, pp.200
...
hal-02271801v1  Journal articles
Anestis Antoniadis, Irène Gijbels, Sophie Lambert-Lacroix, Jean-Michel Poggi. Joint estimation and variable selection for mean and dispersion in proper dispersion models
Electronic Journal of Statistics , Shaker Heights, OH : Institute of Mathematical Statistics, 2016, 10 (1), pp.1630-1676. ⟨10.1214/16-EJS1152⟩
...
hal-02422403v1  Journal articles
Alessandro Benfenati, Emilie Chouzenoux, Jean-Christophe Pesquet. Proximal approaches for matrix optimization problems: Application to robust precision matrix estimation
Signal Processing, Elsevier, 2020, 169, ⟨10.1016/j.sigpro.2019.107417⟩
Designed by Inria-IES Team : http://hal.inria.fr/    Hosted by HAL : http://hal.archives-ouvertes.fr/