Articles citing this article

The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).

Cited article:

Mixed noise and posterior estimation with conditional deepGEM

Paul Hagemann, Johannes Hertrich, Maren Casfor, Sebastian Heidenreich and Gabriele Steidl
Machine Learning: Science and Technology 5 (3) 035001 (2024)
https://doi.org/10.1088/2632-2153/ad5926

Response to ‘Letter to the Editor: on the stability and internal consistency of component-wise sparse mixture regression based clustering’, Zhang et al.

Wennan Chang, Chi Zhang and Sha Cao
Briefings in Bioinformatics 23 (4) (2022)
https://doi.org/10.1093/bib/bbac262

PCA reduced Gaussian mixture models with applications in superresolution

Johannes Hertrich, Dang-Phuong-Lan Nguyen, Jean-Francois Aujol, et al.
Inverse Problems & Imaging 16 (2) 341 (2022)
https://doi.org/10.3934/ipi.2021053

Analysis of a generalised expectation–maximisation algorithm for Gaussian mixture models: a control systems perspective

Sarthak Chatterjee, Orlando Romero and Sérgio Pequito
International Journal of Control 95 (10) 2734 (2022)
https://doi.org/10.1080/00207179.2021.1931964

Max-Affine Regression: Parameter Estimation for Gaussian Designs

Avishek Ghosh, Ashwin Pananjady, Adityanand Guntuboyina and Kannan Ramchandran
IEEE Transactions on Information Theory 68 (3) 1851 (2022)
https://doi.org/10.1109/TIT.2021.3130717

Covert Anti-Jamming Communication Based on Gaussian Coded Modulation

Haeung Choi, Sangjun Park and Heung-No Lee
Applied Sciences 11 (9) 3759 (2021)
https://doi.org/10.3390/app11093759

On the curved exponential family in the Stochastic Approximation Expectation Maximization Algorithm

Vianney Debavelaere and Stéphanie Allassonnière
ESAIM: Probability and Statistics 25 408 (2021)
https://doi.org/10.1051/ps/2021015

The Guedon-Vershynin Semi-definite Programming Approach to Low Dimensional Embedding for Unsupervised Clustering

Stéphane Chrétien, Clément Dombry and Adrien Faivre
Frontiers in Applied Mathematics and Statistics 5 (2019)
https://doi.org/10.3389/fams.2019.00041

Introducing and Comparing Recent Clustering Methods for Massive Data Management in the Internet of Things

Christophe Guyeux, Stéphane Chrétien, Gaby Bou Tayeh, Jacques Demerjian and Jacques Bahi
Journal of Sensor and Actuator Networks 8 (4) 56 (2019)
https://doi.org/10.3390/jsan8040056

Multivariate Myriad Filters Based on Parameter Estimation of Student-$t$ Distributions

Friederike Laus and Gabriele Steidl
SIAM Journal on Imaging Sciences 12 (4) 1864 (2019)
https://doi.org/10.1137/19M1242203

Proximity Operators of Discrete Information Divergences

Mireille El Gheche, Giovanni Chierchia and Jean-Christophe Pesquet
IEEE Transactions on Information Theory 64 (2) 1092 (2018)
https://doi.org/10.1109/TIT.2017.2782789

Statistical guarantees for the EM algorithm: From population to sample-based analysis

Sivaraman Balakrishnan, Martin J. Wainwright and Bin Yu
The Annals of Statistics 45 (1) (2017)
https://doi.org/10.1214/16-AOS1435

A Proximal Point Algorithm for Minimum Divergence Estimators with Application to Mixture Models

Diaa Al Mohamad and Michel Broniatowski
Entropy 18 (8) 277 (2016)
https://doi.org/10.3390/e18080277

A survey on joint tracking using expectation–maximization based techniques

Hua Lan, Xuezhi Wang, Quan Pan, Feng Yang, Zengfu Wang and Yan Liang
Information Fusion 30 52 (2016)
https://doi.org/10.1016/j.inffus.2015.11.008

Majorization-Minimization algorithms for nonsmoothly penalized objective functions

Elizabeth D. Schifano, Robert L. Strawderman and Martin T. Wells
Electronic Journal of Statistics 4 (none) (2010)
https://doi.org/10.1214/10-EJS582