R. Adamczak, A tail inequality for suprema of unbounded empirical processes with applications to Markov chains, Electronic Journal of Probability, vol.13, issue.0, pp.1000-1034, 2008.
DOI : 10.1214/EJP.v13-521

D. W. Andrews, Non-strong mixing autoregressive processes, Journal of Applied Probability, vol.21, issue.04, pp.930-934, 1984.
DOI : 10.2307/3212764

G. Bennett, Probability Inequalities for the Sum of Independent Random Variables, Journal of the American Statistical Association, vol.18, issue.297, pp.33-45, 1962.
DOI : 10.1214/aoms/1177730437

P. Bertail, C. , and S. , Sharp bounds for the tail of functionals of markov chains

O. Catoni, Statistical Learning Theory and Stochastic Optimization, Lecture Notes in Mathematics, vol.1851, 2001.
DOI : 10.1007/b99352
URL : https://hal.archives-ouvertes.fr/hal-00104952

P. Collet, S. Martinez, and B. Schmitt, Exponential inequalities for dynamical measures of expanding maps of the interval, Probability Theory and Related Fields, vol.123, issue.3, pp.301-322, 2002.
DOI : 10.1007/s004400200204

J. Dedecker and C. Prieur, New dependence coefficients: Examples and applications to statistics. Probability Theory and Related Fields, pp.203-235, 2005.

J. Dedecker, C. Prieur, R. De-fitte, and P. , Parametrized Kantorovich-Rubin??tein theorem and application to the coupling of random variables, Dependence in Probability and Statistics, pp.105-121, 2006.
DOI : 10.1007/0-387-36062-X_5

P. Doukhan and . Mixing, of Lecture Notes in Statistics, 1994.

P. Doukhan and S. Louhichi, A new weak dependence condition and applications to moment inequalities. Stochastic Process, Appl, vol.84, issue.2, pp.313-342, 1999.

P. Doukhan and M. Neumann, A bernstein type inequality for times series, Stoch. Proc. Appl, pp.117-124, 2007.

P. Doukhan and O. Wintenberger, Weakly dependent chains with infinite memory. Stochastic Process, Appl, vol.118, pp.1997-2013, 2008.
URL : https://hal.archives-ouvertes.fr/hal-00199890

I. Ibragimov, Some limit theorems for stationary processes. Theory of Probab, Appl, vol.7, pp.349-382, 1962.

I. A. Ibragimov and Y. Linnik, Independent and stationary sequences of random variables, 1971.

A. Joulin and Y. Ollivier, Curvature, concentration and error estimates for Markov chain Monte Carlo, The Annals of Probability, vol.38, issue.6
DOI : 10.1214/10-AOP541

P. Lezaud, Chernoff-type bound for finite Markov chains, The Annals of Applied Probability, vol.8, issue.3, pp.849-867, 1998.
DOI : 10.1214/aoap/1028903453
URL : https://hal.archives-ouvertes.fr/hal-00940907

P. Massart, Concentration Inequalities and Model Selection, Lecture Notes in Mathematics, 2003.

F. Merlevede, M. Peligrad, R. , and E. , Bernstein inequality and moderate deviations under strong mixing conditions
DOI : 10.1214/09-IMSCOLL518
URL : https://hal.archives-ouvertes.fr/inria-00360856

F. Merlevede, M. Peligrad, R. , and E. , A Bernstein type inequality and moderate deviations for weakly dependent sequences, Probability Theory and Related Fields, vol.4, issue.1
DOI : 10.1007/s00440-010-0304-9
URL : https://hal.archives-ouvertes.fr/inria-00358525

E. Nummelin, A splitting technique for Harris recurrent Markov chains, Zeitschrift f???r Wahrscheinlichkeitstheorie und Verwandte Gebiete, vol.29, issue.2, pp.309-318, 1978.
DOI : 10.1007/BF00534764

E. Rio, About the Berry-Esseen Theorem for weakly dependent sequences, Probability Theory and Related Fields, vol.36, issue.2, pp.255-282, 1996.
DOI : 10.1007/BF01247840

E. Rio, Ingalités de hoeffding pour les fonctions lipschitziennes de suites dpendantes. Comptes Rendus de l'Acamédie des Sciences de Paris, Série I, pp.330-905, 2000.

P. Samson, Concentration of measure inequalities for Markov chains and $\Phi$-mixing processes, The Annals of Probability, vol.28, issue.1, pp.416-461, 2000.
DOI : 10.1214/aop/1019160125

G. Viennet, Inequalities for absolutely regular sequences: application to density estimation, Probability Theory and Related Fields, vol.107, issue.4, pp.467-492, 1997.
DOI : 10.1007/s004400050094