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 (since 2008). Part time “Professeur chargé de cours”, Ecole Polytechnique (since 2017).
  * **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.

If you click below, you can find a list of my published papers:

===== 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:poly.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 =====
    * [[world:extra|Please follow the link]]

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