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Technical Report

 

  1. A. Dieuleveut, G. Fort and H-T. Wai. Federated Majorize-Minimization : beyond parameter aggregation (former title: Federated Majorize-Minimization for large scale learning).  1st submission in May 2022;  revised in July 2025.
  2. G. Fort and M. Pereyra. Monte Carlo.  For publication on the « Histoire du Traitement du Signal » webpage of the GRETSI association.  June 2025.
  3. G. Fort, F. Forbes and H.-D. Nguyen. Sequential Sample Average Majorization-Minimization. June 2024, Submitted.
  4. G. Fort, E. Moulines, P. Gach. Fast Incremental Expectation Maximization algorithm: √n iterations for an ε-stationary point ?, March
  5. J. Chevallier and G. Fort. Sampling Nonsmooth Log-Concave Densities: A Comparative Study of Primal-Dual Based Proposal Distributions.  September 2024, Submitted.
  6. P. Abry, J. Chevallier, G. Fort and B. Pascal. Hierarchical Bayesian Estimation of COVID-19 Reproduction Number. September 2024, Submitted.
  7. 2020. HAL-02509621. (submitted to SSP 2020; conference canceled due to CoVID-19; the paper is no more submitted).
  8. J.F. Aujol, C. Dossal, G. Fort, E. Moulines. Rates of Convergence of Perturbed FISTA-based algorithms. July 2019. HAL-02182949.
  9. Y. Atchadé, G. Fort, E. Moulines. On stochastic Proximal-Gradient algorithms. February 2014. ArXiv:1402.2365v1 (part of this paper is unpublished).
  10. G. Fort. Fluid limit-based tuning of some hybrid MCMC samplers. Dec 2007.
  11. C. Andrieu and G. Fort. Explicit control of subgeometric ergodicity. Rapport de Recherche, 05:17, 2005.
  12. G. Fort. Partial Least Squares for classification and feature selection in Microarray gene expression data. Dec. 2004.
  13. 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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