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Contributed, International conf.

  1. 2023 IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing, Herradura, Costa Rica; December 2023.
      • Pandemic intensity estimation from Stochastic Approximation-based Algorithms. [poster.pdf] [photo]
  2. IEEE Statistical Signal Processing Workshop (SSP); virtual; July 2021.
      • The Perturbed Prox-Preconditioned SPIDER algorithm for EM-based large scale learning. [slides.pdf] [video]
  3. International Conference on Acoustics, Speech and Signal Processing (ICASSP); virtual; June 2021
      • GEOM-SPIDER-EM: faster variance reduced Stochastic Expectation Maximization for Nonconvex Finite-Sum Optimization. [poster.pdf][slides.pdf][video]
  4. Neural Information Processing Systems (NeuIPS), conference; virtual; December 2020
    • A Stochastic Path-Integrated Differential EstimatoR EM algorithm [poster.pdf]
  5. IEEE Statistical Signal Processing Workshop (SSP); Freiburg, Germany; June 2018
  6. Sixth IMS-ISBA joint meeting BayesComp at MCMski V; Lenzerheide, Switzerland; January 2015.
  7. International Conference on Scientific Computation and Differential Equations; Valladolid, Spain; September 2013.
    • Convergence of the Wang-Landau algorithm [slides.pdf]
  8. Latent Variable Analysis – Independent Component Analysis (LVA-ICA); Tel-Aviv, Israël; March 2012.
  9. IEEE Statistical Signal Processing workshop (SSP); Nice, France; June 2011.
    • Online Expectation-Maximization algorithm to solve the SLAM problem [poster.pdf]
  10. Workshop « Stochastic Approximation: methodology, theory and applications in statistics »; Bristol, United Kingdom; September 2010.
    • Stochastic Approximation for Adaptive Markov chain Monte Carlo algorithm [slides.pdf]
  11. 2009 INFORMS Applied Probability Sociery conference; Ithaca, USA; July 2009.
  12. INFORMS Applied Probability; Eihdhoven, Netherlands; July 2007.
    • Fluid limit for Hybrid MCMC samplers [slides.pdf]
  13. COMPSTAT’04; Prague, Czeck Republic; August 2004.
    • Ridge Patial Least squares for generalized linear models with binary response. [slides.ps]
  14. 10th-INFORMS Applied Probability conference; Ulm, Germany; July 1999.
    • On the convergence of the MCEM algorithm and other iterative Markov random maps.

 

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