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Pr. Randal DOUC

Professeur
Direction & personnel de support, SOP

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Article dans une revue

2024

ref_biblio
Charly Andral, Randal Douc, Hugo Marival, Christian Robert. The importance Markov Chain. Stochastic Processes and their Applications, 2024, ⟨10.1016/j.spa.2024.104316⟩. ⟨hal-03912132⟩
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https://hal.science/hal-03912132/file/arxiv3_main.pdf BibTex

2023

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Kamélia Daudel, Randal Douc, François Roueff. Monotonic Alpha-divergence Minimisation for Variational Inference. Journal of Machine Learning Research, 2023, 24 (62), pp.1-76. ⟨hal-03164338v2⟩
Accès au texte intégral et bibtex
https://telecom-paris.hal.science/hal-03164338/file/ddr_jmlr_final.pdf BibTex

2022

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M Gerber, Randal Douc. A global stochastic optimization particle filter algorithm. Biometrika, 2022, 109 (4), pp.937-955. ⟨10.1093/biomet/asab067⟩. ⟨hal-04081690⟩
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https://arxiv.org/pdf/2007.04803 BibTex

2021

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Kamélia Daudel, Randal Douc, François Portier. Infinite-dimensional gradient-based descent for alpha-divergence minimisation. Annals of Statistics, 2021, 49 (4), pp.2250 - 2270. ⟨hal-02614605v3⟩
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https://telecom-paris.hal.science/hal-02614605/file/AOS2035.pdf BibTex
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Randal Douc, François Roueff, Tepmony Sim. Necessary and sufficient conditions for the identifiability of observation-driven models. Journal of Time Series Analysis, 2021, 42 (2), pp.140-160. ⟨10.1111/jtsa.12559⟩. ⟨hal-02088860v3⟩
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https://hal.science/hal-02088860/file/ident_genod.pdf BibTex
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Tepmony Sim, Randal Douc, François Roueff. General-order observation-driven models: ergodicity and consistency of the maximum likelihood estimator. Electronic Journal of Statistics , 2021, ⟨10.1214/21-EJS1858⟩. ⟨hal-01383554v3⟩
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https://hal.science/hal-01383554/file/genod2.pdf BibTex

2020

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Randal Douc, Jimmy Olsson, François Roueff. Posterior consistency for partially observed Markov models. Stochastic Processes and their Applications, 2020, 130 (2), pp.733-759. ⟨10.1016/j.spa.2019.03.012⟩. ⟨hal-04081621⟩
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https://arxiv.org/pdf/1608.06851 BibTex

2019

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Randal Douc, Jimmy Olsson. Numerically stable online estimation of variance in particle filters. Bernoulli, 2019, 25 (2), pp.1504 - 1535. ⟨hal-01875162⟩
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2017

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Randal Douc, Konstantinos Fokianos, Éric Moulines. Asymptotic properties of quasi-maximum likelihood estimators in observation-driven time series models. Electronic Journal of Statistics , 2017, 11 (2), pp.2707 - 2740. ⟨10.1214/17-EJS1299⟩. ⟨hal-01575698⟩
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2016

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Randal Douc, François Roueff, Tepmony Sim. The maximizing set of the asymptotic normalized log-likelihood for partially observed Markov chains. The Annals of Applied Probability, 2016, 26 (4), pp.2357 - 2383. ⟨10.1214/15-AAP1149⟩. ⟨hal-01080955v2⟩
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https://hal.science/hal-01080955/file/doumonrou.pdf BibTex

2015

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Randal Douc, François Roueff, Tepmony Sim. Handy sufficient conditions for the convergence of the maximum likelihood estimator in observation-driven models. Lithuanian Mathematical Journal, 2015, 55 (3), pp.367-392. ⟨10.1007/s10986-015-9286-8⟩. ⟨hal-01078073v2⟩
Accès au texte intégral et bibtex
https://hal.science/hal-01078073/file/odconsistency_Hal.pdf BibTex
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Randal Douc, Florian Maire, Jimmy Olsson. On the use of Markov chain Monte Carlo methods for the sampling of mixture models : a statistical perspective. Statistics and Computing, 2015, 25 (1), pp.95 - 110. ⟨10.1007/s11222-014-9526-5⟩. ⟨hal-01262405⟩
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Fredrik Lindsten, Randal Douc, Éric Moulines. Uniform ergodicity of the Particle Gibbs sampler. Scandinavian Journal of Statistics, 2015, 42 (3), pp.775 - 797. ⟨10.1111/sjos.12136⟩. ⟨hal-01257066⟩
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2014

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Mylène Bédard, Randal Douc, Éric Moulines. Scaling analysis of delayed rejection MCMC methods. Methodology and Computing in Applied Probability, 2014, 16 (4), pp.811 - 838. ⟨10.1007/s11009-013-9326-y⟩. ⟨hal-01285497⟩
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Randal Douc, Éric Moulines, Jimmy Olsson. Long-term stability of sequential Monte Carlo methods under verifiable conditions. The Annals of Applied Probability, 2014, 24 (5), pp.1767 - 1802. ⟨10.1214/13-AAP962⟩. ⟨hal-01262408⟩
Accès au bibtex
https://arxiv.org/pdf/1203.6898 BibTex
ref_biblio
Florian Maire, Randal Douc, Jimmy Olsson. Comparison of asymptotic variances of inhomogeneous Markov chains with application to Markov chain Monte Carlo methods. Annals of Statistics, 2014, 42 (4), pp.1483 - 1510. ⟨10.1214/14-AOS1209⟩. ⟨hal-01262407⟩
Accès au bibtex
https://arxiv.org/pdf/1307.3719 BibTex

2013

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Randal Douc, Paul Doukhan, Éric Moulines. Ergodicity of observation-driven time series models and consistency of the maximum likelihood estimator. Stochastic Processes and their Applications, 2013, 123 (7), pp.2620-2647. ⟨10.1016/j.spa.2013.04.010⟩. ⟨hal-00833432⟩
Accès au bibtex
https://arxiv.org/pdf/1210.4739 BibTex
ref_biblio
Cyrille Dubarry, Randal Douc. Calibrating the exponential Ornstein-Uhlenbeck multiscale stochastic volatility model. Quantitative Finance, 2013, pp.1-14. ⟨10.1080/14697688.2012.738929⟩. ⟨hal-00832848⟩
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2012

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Randal Douc, Éric Moulines, Jimmy Olsson. On the long-term stability of bootstrap-type particle filters. IFAC Proceedings Volumes, 2012, 45 (16), pp.1131-1136. ⟨10.3182/20120711-3-BE-2027.00380⟩. ⟨hal-04081636⟩
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ref_biblio
Randal Douc, Mylène Bédard, Éric Moulines. Scaling analysis of multiple-try MCMC methods. Stochastic Processes and their Applications, 2012, 122 (3), pp.758-786. ⟨10.1016/j.spa.2011.11.004⟩. ⟨hal-00772096⟩
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ref_biblio
Randal Douc, Éric Moulines. Asymptotic properties of the maximum likelihood estimation in misspecified hidden Markov models. Annals of Statistics, 2012, 40 (5), pp.2697-2732. ⟨10.1214/12-AOS1047⟩. ⟨hal-00832818⟩
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https://arxiv.org/pdf/1110.0356 BibTex

2011

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Randal Douc, Éric Moulines, Jimmy Olsson, Ramon van Handel. Consistency of the maximum likelihood estimator for general hidden Markov models. Annals of Statistics, 2011, 39 (1), pp.474-513. ⟨10.1214/10-AOS834⟩. ⟨hal-00633451⟩
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https://arxiv.org/pdf/0912.4480 BibTex
ref_biblio
Randal Douc, Christian Robert. A vanilla Rao–Blackwellization of Metropolis–Hastings algorithms. Annals of Statistics, 2011, 39 (1), pp.261-277. ⟨10.1214/10-AOS838⟩. ⟨hal-00375377⟩
Accès au texte intégral et bibtex
https://hal.science/hal-00375377/file/dr09.pdf BibTex
ref_biblio
Randal Douc, Aurélien Garivier, Éric Moulines, Jimmy Olsson. Sequential Monte Carlo smoothing for general state space hidden Markov models. The Annals of Applied Probability, 2011, 21 (6), pp.2109-2145. ⟨10.1214/10-AAP735⟩. ⟨hal-00839311⟩
Accès au bibtex
https://arxiv.org/pdf/1202.2945 BibTex

2010

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Randal Douc, Elisabeth Gassiat-Granier, Benoit Landelle, Éric Moulines. Forgetting of the initial distribution for nonergodic Hidden Markov Chains. The Annals of Applied Probability, 2010, 20 (5), pp.1638 - 1662. ⟨hal-01354770⟩
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2009

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Randal Douc, Gersende Fort, Éric Moulines, Pierre Priouret. Forgetting of the initial distribution for Hidden Markov Models. Stochastic Processes and their Applications, 2009, 119 (4), pp.1235--1256. ⟨hal-00138902⟩
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https://hal.science/hal-00138902/file/DoucFortMoulinesPriouret.pdf BibTex
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Randal Douc, Gersende Fort, Arnaud Guillin. Subgeometric rates of convergence of f-ergodic strong Markov processes. Stochastic Processes and their Applications, 2009, 119 (3), pp.897-923. ⟨10.1016/j.spa.2008.03.007⟩. ⟨hal-00077681⟩
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https://hal.science/hal-00077681/file/dfg.pdf BibTex
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Randal Douc, Eric Moulines, Yaacov Ritov. Forgetting of the initial condition for the filter in general state-space hidden Markov chain: a coupling approach. Electronic Journal of Probability, 2009, 14 (none), ⟨10.1214/EJP.v14-593⟩. ⟨hal-04081648⟩
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ref_biblio
Randal Douc, Gersende Fort, Arnaud Guillin. Subgeometric rates of convergence of f-ergodic strong Markov processes. Stochastic Processes and their Applications, 2009, 119 (3), pp.897 - 923. ⟨10.1016/j.spa.2008.03.007⟩. ⟨hal-01314855⟩
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ref_biblio
Randal Douc, Éric Moulines, Jimmy Olsson. Optimality of the auxiliary particle filter. Probability and Mathematical Statistics, 2009, 29 (1), pp.1-28. ⟨hal-00471534⟩
Accès au texte intégral et bibtex
https://hal.science/hal-00471534/file/29.1.1.pdf BibTex

2008

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Olivier Cappé, Randal Douc, Arnaud Guillin, Jean-Michel Marin, Christian P. Robert. Adaptive Importance Sampling in General Mixture Classes. Statistics and Computing, 2008, 18 (4), pp.447-459. ⟨10.1007/s11222-008-9059-x⟩. ⟨hal-00180669v4⟩
Accès au texte intégral et bibtex
https://hal.science/hal-00180669/file/CDGMR07.pdf BibTex
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Randal Douc, A. Guillin, Jean-Michel Marin, C. P. Robert. Convergence of adaptive mixtures of importance sampling schemes. Statistics and Computing, 2008, 18,, pp.447-459. ⟨hal-00432955⟩
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https://arxiv.org/pdf/0708.0711 BibTex
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Randal Douc, François Roueff, Philippe Soulier. On the existence of some ARCH($\infty$) processes. Stochastic Processes and their Applications, 2008, 118 (5), pp.755-761. ⟨10.1016/j.spa.2007.06.002⟩. ⟨hal-00113157v3⟩
Accès au texte intégral et bibtex
https://hal.science/hal-00113157/file/archrev.pdf BibTex
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Randal Douc, Arnaud Guillin, Éric Moulines. Bounds on regeneration times and limit theorems for subgeometric Markov chains. Annales de l'Institut Henri Poincaré (B) Probabilités et Statistiques, 2008, 44 (2), pp.239 - 257. ⟨10.1214/07-AIHP109⟩. ⟨hal-01372463⟩
Accès au bibtex
https://arxiv.org/pdf/math/0601036 BibTex
ref_biblio
Randal Douc, Éric Moulines. Limit theorems for weighted samples with applications to sequential Monte Carlo methods. Annals of Statistics, 2008, 36 (5), pp.2344 - 2376. ⟨10.1214/07-AOS514⟩. ⟨hal-01372025⟩
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ref_biblio
Jimmy Olsson, Olivier Cappé, Randal Douc, Eric Moulines. Sequential Monte Carlo smoothing with application to parameter estimation in non-linear state space models. Bernoulli, 2008, 14 (1), pp.155-179. ⟨10.3150/07-BEJ6150⟩. ⟨hal-00096080v2⟩
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https://hal.science/hal-00096080/file/bej6150.pdf BibTex

2007

ref_biblio
Randal Douc, Éric Moulines, Philippe Soulier. Computable Convergence Rates for Subgeometrically Ergodic Markov Chains. Bernoulli, 2007, 13 (3), ⟨10.3150/07-BEJ5162⟩. ⟨hal-00013769⟩
Accès au texte intégral et bibtex
https://hal.science/hal-00013769/file/DoucMoulinesSoulier.pdf BibTex

2005

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Randal Douc, A. Guillin, J. Najim. Moderate deviations for particle filtering. The Annals of Applied Probability, 2005, 15 (1B), pp.587-614. ⟨10.1214/105051604000000657⟩. ⟨hal-04081665⟩
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https://arxiv.org/pdf/math/0401058 BibTex

2004

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Randal Douc, Gersende Fort, Éric Moulines, Philippe Soulier. Practical drift conditions for subgeometric rates of convergence. The Annals of Applied Probability, 2004, 14 (3), pp.1353-1377. ⟨10.1214/105051604000000323⟩. ⟨hal-00147616⟩
Accès au bibtex
https://arxiv.org/pdf/math/0407122 BibTex
ref_biblio
Randal Douc, E. Moulines, Jeffrey Rosenthal. Quantitative bounds on convergence of time-inhomogeneous Markov chains. The Annals of Applied Probability, 2004, 14 (4), ⟨10.1214/105051604000000620⟩. ⟨hal-04081669⟩
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ref_biblio
Randal Douc, Éric Moulines, Tobias Rydén. Asymptotic properties of the maximum likelihood estimator in autoregressive models with Markov regime. Annals of Statistics, 2004, 32 (5), ⟨10.1214/009053604000000021⟩. ⟨hal-04081670⟩
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2002

ref_biblio
Olivier Cappe, Randal Douc, Eric Moulines, Christian Robert. On the Convergence of the Monte Carlo Maximum Likelihood Method for Latent Variable Models. Scandinavian Journal of Statistics, 2002, 29 (4), pp.615-635. ⟨10.1111/1467-9469.00309⟩. ⟨hal-04081673⟩
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2001

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Randal Douc, Catherine Matias. Asymptotics of the Maximum Likelihood Estimator for General Hidden Markov Models. Bernoulli, 2001, 7 (3), pp.381. ⟨10.2307/3318493⟩. ⟨hal-04081675⟩
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2000

ref_biblio
Randal Douc, Catherine Matias. Propriétés asymptotiques de l'estimateur de maximum de vraisemblance pour des modèles de Markov cachés généraux. Comptes Rendus de l'Académie des Sciences - Series I - Mathematics, 2000, 330 (2), pp.135-138. ⟨10.1016/s0764-4442(00)00138-5⟩. ⟨hal-04081679⟩
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Communication dans un congrès

2021

ref_biblio
Kamélia Daudel, Randal Douc. Mixture weights optimisation for alpha-divergence variational inference. Advances in Neural Information Processing (NeurIPS), Dec 2021, Online, France. pp.4397--4408, ⟨10.48550/arXiv.2106.05114⟩. ⟨hal-04083262⟩
Accès au texte intégral et bibtex
https://hal.science/hal-04083262/file/NeurIPS-2021-mixture-weights-optimisation-for-alpha-divergence-variational-inference-Paper.pdf BibTex

2012

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Florian Maire, Randal Douc, Sidonie Lefebvre, Éric Moulines. An online learning algorithm for mixture models of deformable templates. MLSP '12 : IEEE International Workshop on Machine Learning for Signal Processing, Sep 2012, Santander, Spain. pp.1-6, ⟨10.1109/MLSP.2012.6349725⟩. ⟨hal-00839430⟩
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2011

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Cyrille Dubarry, Randal Douc. Improving particle approximations of the joint smoothing distribution with linear computational cost. SSP 2011 : Statistical Signal Processing Workshop, Jun 2011, Nice, France. pp.209 - 212, ⟨10.1109/SSP.2011.5967661⟩. ⟨hal-01303713⟩
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ref_biblio
Florian Maire, Sidonie Lefebvre, Éric Moulines, Randal Douc. Aircraft classification with a low resolution infrared sensor. SSP 2011 : Statistical Signal Processing Workshop, Jun 2011, Nice, France. pp.761 - 764, ⟨10.1109/SSP.2011.5967815⟩. ⟨hal-01303722⟩
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2009

ref_biblio
Randal Douc, Aurélien Garivier, Éric Moulines, Jimmy Olsson. Approximation particulaire par FFBS de la loi de lissage pour des HMM dans des espaces d'états généraux. 41èmes Journées de Statistique, SFdS, Bordeaux, 2009, Bordeaux, France, France. ⟨inria-00386750⟩
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https://inria.hal.science/inria-00386750/file/p180.pdf BibTex

2005

ref_biblio
Randal Douc, Olivier Cappé, Eric Moulines. Comparison of Resampling Schemes for Particle Filtering. 2005, pp.64-69. ⟨hal-00005883⟩
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https://hal.science/hal-00005883/file/dcm-ispa2005.pdf BibTex

Chapitre d'ouvrage

2022

ref_biblio
Randal Douc, Éric Moulines, David Stoffer. 6 - AN INTRODUCTION TO STATE SPACE MODELS. Statistics for astrophysics, EDP Sciences, pp.215-258, 2022, ⟨10.1051/978-2-7598-2741-1.c011⟩. ⟨hal-03921403⟩
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2006

ref_biblio
Randal Douc, Eric Moulines, Philippe Soulier. Subgeometric ergodicity of Markov chains. Patrice Bertail, Paul Doukhan, Philippe Soulier. Dependence in probability and statistics, Springer, pp.55--64, 2006, Lecture notes in statistics. ⟨hal-00154180⟩
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https://hal.science/hal-00154180/file/douc_moulines_soulier.pdf BibTex

Ouvrages

2018

ref_biblio
Randal Douc, Eric Moulines, Pierre Priouret, Philippe Soulier. Markov chains. Springer, pp.757, 2018, Operation research and financial engineering, Operation research and financial engineering, 978-3-319-97703-4. ⟨10.1007/978-3-319-97704-1⟩. ⟨hal-02022651⟩
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2014

ref_biblio
Randal Douc, Éric Moulines, David Stoffer. Nonlinear time series : theory, methods and applications with R examples. Chapman et Hall - CRC Press, 2014, Texts in statistical science, Texts in statistical science, 978-1-466-50225-3. ⟨hal-01263245⟩
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Proceedings/Recueil des communications

2007

ref_biblio
Jimmy Olsson, Eric Moulines, Randal Douc. Improving the Performance of the Two-Stage Sampling Particle Filter: A Statistical Perspective. IEEE, pp.284-288, 2007, ⟨10.1109/SSP.2007.4301264⟩. ⟨hal-04081654⟩
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Rapport

2008

ref_biblio
Olivier Cappé, Randal Douc, Arnaud Guillin, Jean-Michel Marin, Christian P. Robert. Adaptive Importance Sampling in General Mixture Classes. [Research Report] RR-6332, INRIA. 2008. ⟨inria-00181474v4⟩
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https://inria.hal.science/inria-00181474/file/RR-6332.pdf BibTex

Pré-publication, Document de travail

2024

ref_biblio
Randal Douc, Alain Durmus, Aurélien Enfroy, Jimmy Olsson. Boost your favorite Markov Chain Monte Carlo sampler using Kac's theorem: the Kick-Kac teleportation algorithm. 2024. ⟨hal-04396793⟩
Accès au bibtex
https://arxiv.org/pdf/2201.05002 BibTex

2023

ref_biblio
Randal Douc, Sylvain Le Corff. Asymptotic convergence of iterative optimization algorithms. 2023. ⟨hal-04000741⟩
Accès au texte intégral et bibtex
https://hal.science/hal-04000741/file/cdlc.pdf BibTex

2019

ref_biblio
Kamélia Daudel, Randal Douc, François Portier, François Roueff. The $f$-divergence expectation iteration scheme. 2019. ⟨hal-02298857⟩
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https://hal.science/hal-02298857/file/ddpr2019.pdf BibTex

2009

ref_biblio
Randal Douc, Eric Moulines, Jimmy Olsson, Ramon van Handel. Consistency of the Maximum Likelihood Estimator for general hidden Markov models. 2009. ⟨hal-00442774⟩
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https://imt.hal.science/hal-00442774/file/dmrvh.pdf BibTex
ref_biblio
Randal Douc, Aurélien Garivier, Éric Moulines, Jimmy Olsson. On the Forward Filtering Backward Smoothing particle approximations of the smoothing distribution in general state spaces models. 2009. ⟨hal-00370685⟩
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https://hal.science/hal-00370685/file/dgarm.pdf BibTex

2007

ref_biblio
Randal Douc, Eric Moulines, Jimmy Olsson. On the auxiliary particle filter. 2007. ⟨hal-00174161⟩
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https://hal.science/hal-00174161/file/APF.pdf BibTex
ref_biblio
Randal Douc, Eric Moulines, Ya'Acov Ritov. Forgetting of the initial condition for the filter in general state-space hidden Markov chain: a coupling approach. 2007. ⟨hal-00193309⟩
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https://hal.science/hal-00193309/file/hmmGSS1.pdf BibTex

2006

ref_biblio
Randal Douc, Arnaud Guillin, Éric Moulines. Bounds on Regeneration Times and Limit Theorems for Subgeometric Markov Chains. 2006. ⟨hal-00016396⟩
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https://hal.science/hal-00016396/file/DoucGuillinMoulines.pdf BibTex

2005

ref_biblio
Randal Douc. Non singularity of the asymptotic Fisher information matrix in hidden Markov models. 2005. ⟨hal-00014504⟩
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https://hal.science/hal-00014504/file/douc.pdf BibTex