Optimal Hoeffding bounds for discrete reversible Markov chains
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We build optimal exponential bounds for the probabilities of large deviations of sums \sum_{k=1}^nf(X_k) where (X_k) is a finite reversible Markov chain and f is an arbitrary bounded function. These bounds depend only on the stationary mean E_πf, the end-points of the support of f, the sample size n and the second largest eigenvalue λof the transition matrix.