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Invited, International conf.

    1. (plenary speaker) Monte Carlo and Quasi-Monte Carlo methods in Scientific Computing, Waterloo, Canada, August 2024.
      • TBA
    2. (plenary speaker) - French-German-Spanish conference on Optimization, Gijon, Spain, June 2024.
      • TBA
    3. European Meeting of Statisticians; Warsaw, Poland, July 2023
      • Stochastic Approximation beyond Gradient [slides.pdf]<
    4. Conference « Processus markoviens, semi-markoviens et leurs applications »; Montpellier, France, June 2023
      • When Markov chains control Monte Carlo sampling. [slides.pdf]
    5. Conference « Learning and Optimization in Luminy », CIRM; Marseille, France, October 2022
      • Stochastic Variable Metric Forward-Backward with variance reduction for non-convex optimization [slides.pdf]
    6. Workshop « Current developments in MCMC methods », Banach Center; Warsaw, Poland; December 2021.
      • Federated Expectation Maximization with heterogeneity mitigation and variance reduction.  [slides.pdf]
    7. Conference « Future Synergies for Stochastic and Learning algorithms », CIRM; Marseille, France; September 2021
    8. Conference in Numerical Probability, in honour of Gilles Pagès; Paris, France; September 2020 (postponed in May 2021)
      • A Variance Reduced Expectation Maximization algorithm for finite-sum optimization [slides.pdf] and video
    9. Conference « Structural Inference in High Dimensional Models »; Bordeaux, France; August 2020 (Canceled, Covid19)
    10. Summer School 2020, Indo-French Centre for Applied Mathematics; Bangalore, India; July 2020 (Canceled, Covid19)
    11. Conference « Optimization for Machine Learning », CIRM; Marseille, France; March 2020
      • Fast Incremental Expectation Maximization algorithm: how many iterations for an \epsilon-stationary point ? [slides.pdf]
    12. (plenary speaker) BayesComp 2020; Gainesville, USA; January 2020.
      • invitation declined for professional duties (new schedule of a HCERES evaluation). 
    13. (3 lectures and a talk) Advances in Applied Probability (ICTS Program); Bengaluru, India; August 2019.
    14. (plenary speaker) Twelth International Conference on Monte Carlo methods and Applications (MCM2019); Sydney, Australie; July 2019.
    15. Workshop « The mathematics of imaging »; Paris, France; February 2019.
      • Stochastic Approximation-based algorithms, when the Monte Carlo bias does not vanish [slides.pdf] [video]
    16. Workshop « Computational Statistics and Molecular Simulations: a practical cross-fertilization », BIRS; Oaxaca, Mexico; November 2018.
      • Convergence and Efficiency of Adaptive Importance Sampling techniques with partial biasing [slides.pdf] [video]
    17. Workshop « Operator Splitting methods in Data Analysis »; Raleigh, USA; March 2018.
      • Perturbed (accelerated) Proximal-Gradient Algorithms [slides.pdf]
    18. Foundations of Computational Mathematics (FOCM), Workshop « Stochastic Computation »; Barcelona, Spain; July 2017.
      • Beyond Well-tempered Metadynamics algorithms for sampling multimodal target densities [slides.pdf]
    19. 11th International Conference on Monte Carlo methods and Applications; Montreal, Canada; July 2017.
      • MCMC design-based non-parametric regression for rare-event. Application to nested rosk computations [slides.pdf]
    20. International Conference on Monte Carlo techniques (closing conferene of a thematic cycle); Paris, France; July 2016.
      • Nested risk computations through non parametric regression with Markovian design [slides.pdf]
    21. Workshop « Stochastic Algorithms for Big Data »; Paris, France; July 2016. 
      • Stochastic Perturbations of Proximal-Gradient methods for non-smooth convex optimization: the price of Markovian perturbations  [slides.pdf]
    22. Workshop « High Dimensional Statistical Models & Big Data », Alan Turing Institute; London, United Kingdom; February 2016.
      • Convergence of Perturbed Gradient-based methods for non-smooth convex optimization [slides.pdf]
    23. Workshop « Free energy calculations: a mathematical perspective », BIRS; Oaxaca, Mexico; July 2015.
      • Mathematical aspects of adaptive samplers: application to free energy calculation. [slides.pdf][video][photo]
    24. International Conference « 7th Journées de Statistique du Sud »; Barcelona, Spain; June 2014.
      • Sampling multimodal densities on large dimensional spaces [slides.pdf][photo]
    25. Workshop « Computational methods for statistical mechanics »; Edinburgh, United Kingdom; July 2014.
      • Convergence and Efficiency of the Wang Landau algorithm [slides.pdf]
    26. Workshop « From spectral gap to particle filters »; Reading, United Kingdom; September 2013.
      • Adaptive and Interacting Markov chain Monte Carlo [slides.pdf]
    27. Workshop « New directions in Monte Carlo methods »; Gainesville, USA; January 2013.
      • Convergence and Efficiency of the Wang Landau algorithm [slides.pdf][photo]
    28. Workshop « Big Bang, Big Data, Big Computers »; Paris, France; September 2012.
      • Adaptive abd Interacting Monte Carlo methods for bayesian analysis [slides.pdf]
    29. ISBA conference 2012; Kyoto, Japan; June 2012.
    30. Workshop « Advances in Markov chain Monte Carlo »; Edinburgh, United Kingdom; April 2012.
      • Stochastic Approximation-based adaptation for Interacting MCMC [slides.pdf]
    31. Workshop  « Challenges and Advances in High Dimensional and High Complexity Monte Carlo Computation and Theory »; Calgary, Canada; March 2012.
      • Parallel Tempering and interacting algorithms – Part II: adaptive equi-enery samplers [slides.pdf][photo]
    32. Conference MCQMC 2010; Warsaw, Poland; August 2010.
      • Convergence of Adaptive and Interacting MCMC algorithms [slides.pdf]
    33. Conference « Optimization in MCMC »; Warwick, United Kingdom; June 2009.
      • Adaptive MCMC: theory and methods [slides.pdf]
    34. Congrès SSC-SFDS; Ottawa, Canada; May 2008.
      • Stability of Markov chains based on fluid limit techniques. Applications to MCMC [slides.pdf]
    35. ADAP’ski; Bormio, Italy; January 2008.
      • Fluid limit-based tuning of some hybrid MCMC samplers [slides.pdf]
    36. Workshop « New developments in MCMC: diffusions, images and other challenges »; Warwick, United Kingdom; August 2006.
      • Criteria for subgeometric ergodicity of strong Markov processes [slides.pdf]
    37. Workshop « MCMC methodology »; Lancaster, United Kingdom; December 2001.
      • Talk 1 « Some recent results on Hybrid samplers » [slides.ps]
    38. Workshop « MCMC methodology »; Lancaster, United Kingdom; December 2001.
      • Talk 2 « Convergence of the MCEM algorithm » [slides.ps]
    39. European conference on Spatial and Computational Statistics; Ambleside, United Kingdom; September 2000.

 

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