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Technical Report

  1. A. Dieuleveut, G. Fort and H-T. Wai. Federated Majorize-Minimization for large scale learning.  May 2022, Submitted. 
  2. G. Fort, E. Moulines, P. Gach. Fast Incremental Expectation Maximization algorithm: √n iterations for an ε-stationary point ?, March 2020. HAL-02509621. (submitted to SSP 2020; conference canceled due to CoVID-19; the paper is no more submitted).
  3. J.F. Aujol, C. Dossal, G. Fort, E. Moulines. Rates of Convergence of Perturbed FISTA-based algorithms. July 2019. HAL-02182949.
  4. Y. Atchadé, G. Fort, E. Moulines. On stochastic Proximal-Gradient algorithms. February 2014. ArXiv:1402.2365v1 (part of this paper is unpublished).
  5. G. Fort. Fluid limit-based tuning of some hybrid MCMC samplers. Dec 2007.
  6. C. Andrieu and G. Fort. Explicit control of subgeometric ergodicity. Rapport de Recherche, 05:17, 2005.
  7. G. Fort. Partial Least Squares for classification and feature selection in Microarray gene expression data. Dec. 2004.
  8. G. Fort. Computable bounds for V-geometric ergodicity of Markov transition kernels. Rapport de Recherche, Univ. J. Fourier, RR 1047-M.

 

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