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We present new concentration of measure inequalities for Markov chains, generalising results for chains that are contracting in Wasserstein distance. These are particularly suited to establishing the cut-off phenomenon for suitable chains.…

Probability · Mathematics 2022-05-24 Andrew Barbour , Graham Brightwell , Malwina Luczak

Li and Hu recently established variance-type O(1/n) bounds for the sample mean of independent random vectors under sublinear expectations. We extend their results to the exponential concentration regime. For bounded, independent R^d-valued…

Statistics Theory · Mathematics 2026-02-26 Nahom Seyoum

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…

Probability · Mathematics 2007-05-23 Carlos A. Leon , Francois Perron

The martingale method is used to establish concentration inequalities for a class of dependent random sequences on a countable state space, with the constants in the inequalities expressed in terms of certain mixing coefficients. Along the…

Probability · Mathematics 2009-01-22 Leonid , Kontorovich , Kavita Ramanan

We provide a general framework for computing upper bounds on mixing times of finite Markov chains when its minimal ideal is left zero. Our analysis is based on combining results by Brown and Diaconis with our previous work on stationary…

Probability · Mathematics 2023-01-04 John Rhodes , Anne Schilling

An irreversible Markov-chain Monte Carlo (MCMC) algorithm with skew detailed balance conditions originally proposed by Turitsyn et al. is extended to general discrete systems on the basis of the Metropolis-Hastings scheme. To evaluate the…

Statistical Mechanics · Physics 2016-04-21 Yuji Sakai , Koji Hukushima

Markov chain Monte Carlo (MCMC) methods generate samples that are asymptotically distributed from a target distribution of interest as the number of iterations goes to infinity. Various theoretical results provide upper bounds on the…

Computation · Statistics 2019-10-30 Niloy Biswas , Pierre E. Jacob , Paul Vanetti

We derive new concentration bounds for time averages of measurement outcomes in quantum Markov processes. This generalizes well-known bounds for classical Markov chains which provide constraints on finite time fluctuations of time-additive…

Quantum Physics · Physics 2023-07-19 Federico Girotti , Juan P. Garrahan , Mădălin Guţă

We introduce a framework for obtaining tight mixing times for Markov chains based on what we call restricted modified log-Sobolev inequalities. Modified log-Sobolev inequalities (MLSI) quantify the rate of relative entropy contraction for…

Data Structures and Algorithms · Computer Science 2021-11-08 Nima Anari , Vishesh Jain , Frederic Koehler , Huy Tuan Pham , Thuy-Duong Vuong

In this paper, we provide sufficient conditions for the existence of the invariant distribution and for subgeometric rates of convergence in Wasserstein distance for general state-space Markov chains which are (possibly) not irreducible.…

Probability · Mathematics 2015-07-15 Alain Durmus , Gersende Fort , Eric Moulines

The ensemble of random Markov matrices is introduced as a set of Markov or stochastic matrices with the maximal Shannon entropy. The statistical properties of the stationary distribution pi, the average entropy growth rate $h$ and the…

Statistics Theory · Mathematics 2015-05-13 Martin Horvat

We show that the joint spectral radius of a finite collection of nonnegative matrices can be bounded by the eigenvalue of a non-linear operator. This eigenvalue coincides with the ergodic constant of a risk-sensitive control problem, or of…

Optimization and Control · Mathematics 2018-05-10 Stephane Gaubert , Nikolas Stott

We prove a version of McDiarmid's bounded differences inequality for Markov chains, with constants proportional to the mixing time of the chain. We also show variance bounds and Bernstein-type inequalities for empirical averages of Markov…

Probability · Mathematics 2018-11-14 Daniel Paulin

In this paper, we establish novel concentration inequalities for additive functionals of geometrically ergodic Markov chains similar to Rosenthal inequalities for sums of independent random variables. We pay special attention to the…

Probability · Mathematics 2025-09-26 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov , Marina Sheshukova

We present some extensions of Bernstein's concentration inequality for random matrices. This inequality has become a useful and powerful tool for many problems in statistics, signal processing and theoretical computer science. The main…

Probability · Mathematics 2017-04-18 Stanislav Minsker

We derive explicit Bernstein-type and Bennett-type concentration inequalities for matrix-valued martingale processes with unbounded observations from the Hermitian space $\mathbb{H}(d)$. Specifically, we assume that the…

Probability · Mathematics 2025-02-21 Alexey Kroshnin , Alexandra Suvorikova

This paper studies the estimation of low-rank Markov chains from empirical trajectories. We propose a non-convex estimator based on rank-constrained likelihood maximization. Statistical upper bounds are provided for the Kullback-Leiber…

Machine Learning · Statistics 2018-07-20 Xudong Li , Mengdi Wang , Anru Zhang

Let $\{Y_i\}_{i=1}^{\infty}$ be a stationary reversible Markov chain with state space $[N]$, let $(X, \| \cdot \|)$ be a real-valued Banach space and let $f_1, \ldots, f_n: [N] \rightarrow X$ be functions with mean $0$ such that $\|f_i(v)\|…

Probability · Mathematics 2026-03-02 Shravas Rao

We consider bounds on the convergence of Ritz values from a sequence of Krylov subspaces to interior eigenvalues of Hermitean matrices. These bounds are useful in regions of low spectral density, for example near voids in the spectrum, as…

Numerical Analysis · Mathematics 2011-10-18 Chris Johnson , A. D. Kennedy

This paper develops nonasymptotic growth and concentration bounds for a product of independent random matrices. These results sharpen and generalize recent work of Henriksen-Ward, and they are similar in spirit to the results of…

Probability · Mathematics 2020-03-12 De Huang , Jonathan Niles-Weed , Joel A. Tropp , Rachel Ward