Welcome to Randal Douc's wiki

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====== Welcome to Randal Douc's homepage ======


{{ :world:randaldoucjuillet2021.jpg?200|}}
  * **Current position**: Full professor at Telecom Sudparis (2008-current). 
  * **Former position**: 
    * Full time position: "Professeur chargé de cours", Ecole Polytechnique, 2001-2007. 
    * Part-time position: “Professeur chargé de cours”, Ecole Polytechnique, 2017-2023.
  * **Area of Interest**: Computational Statistics, Applied Probability, Machine Learning.
  * **Keywords**: Hidden Markov Models, latent variable models, sequential Monte Carlo methods, Markov chains Monte Carlo, variational inference, statistical inference.
  * **Email:**   
      - randal.douc"arobase"telecom-sudparis.eu 
      - randal.douc"arobase"polytechnique.edu


===== Publications =====

I  co-authored the following two books:

  - **Book**: R. Douc, E. Moulines and D. Stoffer: Non Linear Time series: //Theory, Methods and Applications with R Examples.// Wiley Edition, 2014.
  - **Book**: R. Douc, E. Moulines, P. Priouret and P. Soulier: //Markov chains.// Springer Edition, 2018.

 <color /yellow> If you click below, you can find a list of my published papers: </color>

 <hidden ====Click here to see my published papers====>  
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<searchtable>
^ Id  ^ Authors                                                                     ^ Title                                                                                                                    ^ Journal                                                       ^ Year           ^ References                                          ^ Links  ^
| 1   | R. Douc, C. Matias                                                          | Propriétés asymptotiques de l'estimateur de maximum de vraisemblance pour des modèles de Markov cachés généraux          | C.R Académie des Sciences                                     | 2000           |                                  Série I, p.135-138 |        |
| 2   | R. Douc, C. Matias                                                          | Asymptotics of the Maximum Likelihood Estimator for general Hidden Markov Models                                         | Bernoulli                                                     | 2001           |                           Volume 7, no. 3, 381--420 |        |
| 3   | O.Cappé, R.Douc, E.Moulines, C.Robert.                                      | On the Convergence of the Monte-Carlo Maximum Likelihood for Latent Variable Models                                      | Scandinavian Journal of Statistics                            | 2002           |                       Volume 29 issue 4, p. 615-635 |        |
| 4   | R.Douc, E. Moulines, J. Rosenthal.                                          | Quantitative bounds for geometric convergence rates of Markov chains                                                     | Annals of Applied Probability                                 | 2004           |                         Volume 14, no. 4, 1643-1665 |        |
| 5   | R. Douc, G. Fort, E. Moulines, P. Soulier.                                  | Practical drift conditions for subgeometric rates of convergence                                                         | Annals of Applied Probability                                 | 2004           |                 Volume 14, no. 3, 1353--1377. 60J10 |        |
| 6   | R. Douc, E. Moulines, T. Ryden                                              | Asymptotic properties of the maximum likelihood estimator in autoregressive models with Marko                            | Annals of Statistics                                          | 2004           |                        Volume 32 , no. 5, 2254-2304 |        |
| 7   | R. Douc, A. Guillin and J. Najim                                            | Moderate deviation in particle filtering                                                                                 | Annals of Applied Probability                                 | 2005           |                         Volume 15 , no. 1B, 587-614 |        |
| 8   | R. Douc, E. Moulines and P. Soulier                                         | Computable bounds for subgeometric ergodic Markov chains                                                                 | Bernoulli                                                     | 2007           |                       Volume 13, Number 3 , 831-848 |        |
| 9   | R. Douc, A. Guillin, J.M. Marin, C.P. Robert                                | Minimum variance importance sampling via Population Monte Carlo                                                          | Esaim P&S.                                                    | 2007           |                              Volume 11, pp. 427-447 |        |
| 10  | R. Douc, A. Guillin, J.M. Marin, C.P. Robert.                               | Convergence of adaptive mixtures of importance sampling schemes                                                          | Annals of Statistics                                          | 2007           |                                Volume 35, Number 1. |        |
| 11  | O. Cappé, R. Douc, A. Guillin, J. M. Marin and C. Robert                    | Adaptive importance sampling in general mixture classes                                                                  | Statistics and Computing                                      | 2008           |                        Volume 18, Number 4, 447-459 |        |
| 12  | O. Cappé, R. Douc, E. Moulines and J. Olsson.                               | Sequential Monte Carlo smoothing with application to parameter estimation in non linear state space models               | Bernoulli.                                                    | 2008           | Volume 14, Number 1 , 155-179.                      |        |
| 13  | R. Douc, A. Guillin and E. Moulines.                                        | Bounds on regeneration times and limit theorems for subgeometric Markov chains                                           | Annales de l'I.H.P                                            | 2008           | Volume 44, Number 2, 239-257.                       |        |
| 14  | R.Douc and E. Moulines                                                      | Limit theorems for weighted samples with applications to Sequential Monte Carlo Methods                                  | Annals of Statistics                                          | 2008           | Volume 36, Number 5 , 2344-2376                     |        |
| 15  | R. Douc, F. Roueff and P. Soulier                                           | On the existence of ARCH(infini) processes                                                                               | Stochastic Processes and their Applications                   | 2008           | Volume 118, Issue 5, 755-761                        |        |
| 16  | R. Douc, G. Fort, E. Moulines and P. Priouret                               | Forgetting of the initial distribution for Hidden Markov Models                                                          | Stochastic Processes and their Applications                   | 2009           | Volume 119, Number 4, Pages 1235-1256               |        |
| 17  | R.Douc, E. Moulines and J. Olsson                                           | Optimality of the auxillary particle filter                                                                              | Probability and Mathematical Statistics.                      | 2009           | Volume 29, issue 1, pages 1-28                      |        |
| 18  | R. Douc, G. Fort and A. Guillin                                             | Subgeometric rates of convergence of f-ergodic strong Markov processes                                                   | Stochastic Processes and their Applications.                  | 2009           | Volume 119 Number 3, 897-923.                       |        |
| 19  | R. Douc, E. Moulines and Y. Ritov.                                          | Forgetting of the initial condition for the filter in general state-space hidden Markov chain: a coupling approach       | Electronic Journal of Probability                             | 2009           | Volume 14, pp 27-49.                                |        |
| 20  | R. Douc, E. Gassiat, B. Landelle, E. Moulines                               | Forgetting the initial distribution in non-ergodic Hidden Markov models                                                  | Annals of Applied Probability                                 | 2010           | Volume 20, Number 5, 1638-1662.                     |        |
| 21  | R. Douc, E. Moulines, J. Olsson and R. Van Handel                           | Consistency of the maximum likelihood estimator for general hidden Markov models                                         | Annals of Statistics                                          | 2011           | Volume 39, Number 1, 474-513.                       |        |
| 22  | R. Douc, C.P. Robert                                                        | A vanilla Rao-Blackwellisation of Metropolis Hastings algorithms                                                         | Annals of Statistics                                          | 2011           | Volume 39, Number 1, 261-277                        |        |
| 23  | R. Douc, A. Garivier, E. Moulines, J. Olsson.                               | Sequential Monte Carlo smoothing for general state space hidden Markov models                                            | Annals of Applied Probability                                 | 2011           | Volume 21, Number 6 (2011), 2109-2145               |        |
| 24  | M. Bédard, R. Douc and E. Moulines                                          | Scaling analysis of multiple-try MCMC methods                                                                            | Stochastic Processes and their Applications                   | 2012           | Volume 122, Issue 3, Pages 758-786                  |        |
| 25  | R. Douc and E. Moulines                                                     | Asymptotic properties of the maximum likelihood estimation in misspecified Hidden Markov models                          | Annals of Statistics                                          | 2012           | Oct. 2012, Volume 40, Number 5 (2012), 2697-2732.   |        |
| 26  | R. Douc, P. Doukhan and E. Moulines                                         | Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator                  | Stochastic Processes and their Applications                   | 2013           | Volume 123, Issue 7, July 2013, Pages 2620-2647     |        |
| 28  | M. Bédard, R. Douc and E. Moulines                                          | Scaling analysis of Delayed Rejection MCMC methods                                                                       | Methodology and Computing in Applied Probability              | 2014           | Volume 16, Issue 4, P 811-838                       |        |
| 27  | C. Dubarry, R. Douc                                                         | Calibrating the exponential Ornstein-Uhlenbeck multiscale stochastic volatility model                                    | Quantitative finance                                          | 2013           | Volume 14, Issue 3, p 443-456                       |        |
| 29  | R. Douc, E. Moulines and J. Olsson                                          | Long-term stability of sequential Monte Carlo methods under verifiable conditions                                        | Annals of Applied Probability                                 | 2014           | Volume 24, No. 5, p 1767–1802                       |        |
| 30  | F. Maire, R. Douc, J. Olsson                                                | Comparison of Asymptotic Variances of Inhomogeneous Markov Chains with Applications to Markov Chain Monte Carlo Methods  | Annals of Statistics                                          | 2014           | Volume 42, No. 4, p 1483–1510                       |        |
| 31  | R. Douc, J. Olsson and F. Maire                                             | On the use of Markov chain Monte Carlo methods for the sampling of mixture models                                        | Statistics and Computing                                      | 2015           | Volume 25, Issue 1, pp 95-110                       |        |
| 32  | R. Douc, F. Roueff and T. Sim                                               | Handy sufficient conditions for the convergence of the maximum likelihood estimator in observation-driven models         | Lituanian Mathematical Journal                                | 2015           | Volume 55, Issue 3, pp 367-392                      |        |
| 33  | R. Douc, F. Lindsten and E. Moulines                                        | Uniform ergodicity of the Particle Gibbs sampler                                                                         | Scandinavian Journal of Statistics                            | 2015           | Volume 42, Issue 3, pp 775-797                      |        |
| 34  | R. Douc, F. Roueff and T. Sim                                               | The maximizing set of the asymptotic normalized log-likelihood for partially observed Markov chains                      | Annals of Applied probability                                 | 2016           | Volume 26, Number 4, 2357-2383.                     |        |
| 35  | R. Douc, K. Fokianos and E. Moulines                                        | Asymptotic properties of Quasi-Maximum Likelihood Estimators in Observation-Driven Time Series models                    | Electronic Journal of Statistics                              | 2017           | Volume 11, Number 2 (2017), 2707-2740.              |        |
| 36  | R. Douc and J. Olsson                                                       | Numerically stable online estimation of variance in particle filters                                                     | Bernoulli                                                     | 2019           | Volume 25, Number 2, 1504-1535                      |        |
| 37  | R. Douc, J. Olsson and F. Roueff                                            | Posterior consistency for partially observed Markov models                                                               | Stochastic Processes and their applications                   | 2020           | Volume 130, Issue 2, february 2020, Pages 733-759   |        |
| 38  | R. Douc, F. Roueff and T. Sim                                               | Necessary and sufficient conditions for the identifiability of observation-driven models                                 | Journal of Time Series Analysis (JTSA)                        | 2021           | Volume 42, Issue 2, p140-160                        |        |
| 39  | R. Douc, F. Roueff, T. Sim                                                  | General-order observation-driven models: Ergodicity and consistency of the maximum likelihood estimator                  | Electronic Journal of Statistics                              | 2021           | Vol. 15, No. 1, 3349-3393                           |        |
| 40  | K. Daudel, R. Douc, F. Portier                                              | Infinite-dimensional gradient-based descent for alpha-divergence minimisation                                            | Annals of Statistics                                          | 2021           | Vol. 49, No. 4, 2250–2270                           |        |
| 41  | K. Daudel, R. Douc                                                          | Mixture weights optimisation for Alpha-Divergence Variational Inference                                                  | Advances in Neural Information Processing Systems, (Neurips)  | 2021.\\  Nov.  | 34                                                  |        |
| 42  | M. Gerber, R. Douc                                                          | A Global Stochastic Optimization Particle Filter Algorithm                                                               | Biometrika                                                    | 2022           | Volume 109, Issue 4, December 2022, Pages 937–955.  |        |
| 43  | K. Daudel, R. Douc, F. Roueff                                               | Monotonic alpha-divergence minimisation                                                                                  | Journal of Machine Learning Research (JMLR)                   | 2023           | (62):1−76, 2023. Vol 24.                            |        |
| 44  | C. Andral, R. Douc, C.P. Robert                                             | The Importance Markov chain                                                                                              | Stochastic Processes and their applications                   | 2024           | Vol 171, May 2024.                                  |        |
| 45  | F. Bertholom, R. Douc, F. Roueff                                            | Asymptotics of Alpha-Divergence Variational Inference Algorithms with Exponential Families                               | Advances in Neural Information Processing Systems, (Neurips)  | 2024           | 37                                                  |        |
| 46  | B. Moufad, Y. Janati, L. Bedin, A. Durmus, R. Douc, J. Olsson, E. Moulines  | Variational Diffusion Posterior Sampling with Midpoint Guidance                                                          | ICLR                                                          | 2025           |                                                     |        |
| 47  | R. Douc, P. E. Jacob, A. Lee, D. Vats                                       | Solving the Poisson equation using coupled Markov chains                                                                 | Annals of Statistics                                          | 2025           | Accepted.                                           |        |
| 48  | Y. Chen, M. Gerber, C. Andrieu, R. Douc                                     | Self-Organizing State-Space Models with Artificial Dynamics                                                              | Submitted. [[https://arxiv.org/abs/2409.08928|Arxiv]]         | 2025           |                                                     |        |
| 49  | R. Douc, A. Durmus, A. Enfroy, J. Olsson                                    | Boost your favorite Markov Chain Monte Carlo sampler using Kac's theorem: the Kick-Kac teleportation algorithm           | Submitted. [[https://arxiv.org/abs/2201.05002|Arxiv]]         |                |                                                     |        |
| 50  | R. Douc, S. Le Corff                                                        | Asymptotic convergence of iterative optimization algorithms                                                              | Submitted. [[https://arxiv.org/pdf/2302.12544.pdf|Arxiv]]     |                |                                                     |        |
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===== Teaching materials =====


^  Name of the Course                                          ^  Description                     ^  Lecture Notes                                        ^  Useful links and keywords                                                               ^ Miscellanous  ^
| Chaînes de Markov                                            | Cours M2 dans le master MDA      |                                                       | [[world:markovchains|A course on Markov Chains: Advanced topics]]                        |               |
| Eléments d'analyse et théorie de l'intégration               | Cours tronc commun TSP           | {{ :world:polymaths.pdf | Lecture Notes}}             | Measure, Integration, Residues theorem, Hilbert space, Fourier transform                 |               |
| Monte Carlo and advanced sampling methods                    | Majeure MSA, TSP. ITC.           | {{ :world:polymcenglish.pdf | Lecture Notes}}         | Rejection, Importance Sampling, Control Variates, Stratification, Variance reduction     |               |
| Introduction to the Extreme Value Theory                     | Majeure MSA, TSP.                | {{ :world:polyxtremes.pdf | Lecture Notes}}           | Order Statistics, Fisher-Tippett-Gnedenko theorem, domain of attraction                  |               |
| Stochastic calculus for finance                              | Majeure MSA, TSP                 | {{ :world:polycalculstofinance.pdf | Lecture Notes}}  | Ito Calculus, stochastic integrals, stochastic differential equations, brownian motions  |               |
| Monte Carlo with applications to finance                     | Majeure MSA, TSP                 | {{ :world:polymcfinanceenglish.pdf | Lecture Notes}}  | Brownian bridges, monte carlo, variance reduction, Euler schemes                         |               |
| Markov Chain Monte Carlo: Theory and Practical applications  | Master M2DS                      | {{ :world:polymcmc.pdf | Lecture Notes}}                  | Mcmc methods, Metropolis Hastings, Pseudo marginal algorithms, Hamiltonian Monte Carlo   |               |
| Fundations of Machine Learning                               | 3rd year, Ecole Polytechnique    |                                                       |                                                                                          |               |
| Aléatoire                                                    | 1ère année, Ecole Polytechnique  |                                                       |                                                                                          |               |


===== Education =====
    * [[world:education|Please follow the link]]

===== Extra (Theater, Movies) =====
    * [[world:extra|Please follow the link]]
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