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This paper studies Hoeffding's inequality for Markov chains under the generalized concentrability condition defined via integral probability metric (IPM). The generalized concentrability condition establishes a framework that interpolates…

Machine Learning · Statistics 2023-10-06 Hao Chen , Abhishek Gupta , Yin Sun , Ness Shroff

We establish Chernoff-type bounds for the largest eigenvalue of sums of Hermitian random matrices generated by a time-inhomogeneous Markov chain. Our primary regime assumes a compact state space and contractivity of each Markov kernel in…

Probability · Mathematics 2026-05-26 Luca Zanetti

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 prove an apparently novel concentration of measure result for Markov tree processes. The bound we derive reduces to the known bounds for Markov processes when the tree is a chain, thus strictly generalizing the known Markov process…

Probability · Mathematics 2007-05-23 Leonid Kontorovich

We prove a Chernoff-type bound for sums of matrix-valued random variables sampled via a regular (aperiodic and irreducible) finite Markov chain. Specially, consider a random walk on a regular Markov chain and a Hermitian matrix-valued…

Machine Learning · Statistics 2020-10-30 Jiezhong Qiu , Chi Wang , Ben Liao , Richard Peng , Jie Tang

Let $\{W_t\}_{t=1}^{\infty}$ be a finite state stationary Markov chain, and suppose that $f$ is a real-valued function on the state space. If $f$ is bounded, then Gillman's expander Chernoff bound (1993) provides concentration estimates for…

Probability · Mathematics 2019-06-19 Assaf Naor , Shravas Rao , Oded Regev

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

We investigate the problem of quantifying contraction coefficients of Markov transition kernels in Kantorovich ($L^1$ Wasserstein) distances. For diffusion processes, relatively precise quantitative bounds on contraction rates have recently…

Probability · Mathematics 2018-08-22 Andreas Eberle , Mateusz B. Majka

We consider symmetric Markov chains on $\Bbb Z^d$ where we do {\bf not} assume that the conductance between two points must be zero if the points are far apart. Under a uniform second moment condition on the conductances, we obtain upper…

Probability · Mathematics 2007-05-23 Richard F. Bass , Takashi Kumagai

For Markov chains and Markov processes exhibiting a form of stochastic monotonicity (larger states shift up transition probabilities in terms of stochastic dominance), stability and ergodicity results can be obtained using order-theoretic…

Probability · Mathematics 2024-10-01 Takashi Kamihigashi , John Stachurski

We prove a new concentration inequality for U-statistics of order two for uniformly ergodic Markov chains. Working with bounded and $\pi$-canonical kernels, we show that we can recover the convergence rate of Arcones and Gin{\'e} who proved…

Probability · Mathematics 2022-03-21 Quentin Duchemin , Yohann de Castro , Claire Lacour

For a wide class of monotonic functions $f$, we develop a Chernoff-style concentration inequality for quadratic forms $Q_f \sim \sum\limits_{i=1}^n f(\eta_i) (Z_i + \delta_i)^2$, where $Z_i \sim N(0,1)$. The inequality is expressed in terms…

Statistics Theory · Mathematics 2019-11-14 Robert E. Gallagher , Louis J. M. Aslett , David Steinsaltz , Ryan R. Christ

We provide explicit expressions for the constants involved in the characterisation of ergodicity of sub-geometric Markov chains. The constants are determined in terms of those appearing in the assumed drift and one-step minorisation…

Probability · Mathematics 2014-03-18 Christophe Andrieu , Gersende Fort , Matti Vihola

Let $(\xi_n)_{n=0}^\infty$ be a nonhomogeneous Markov chain taking values from finite state-space of $\mathbf{X}=\{1,2,\ldots,b\}$. In this paper, we will study the generalized entropy ergodic theorem with almost-everywhere and…

Probability · Mathematics 2015-01-19 Zhongzhi Wang , Weiguo Yang

We establish a new Bernstein-type deviation inequality for general (non-reversible) discrete-time Markov chains via an elementary approach. More robust than existing works in the literature, our result only requires the Markov chain to…

Probability · Mathematics 2025-10-07 De Huang , Xiangyuan Li

The data processing inequality is central to information theory and motivates the study of monotonic divergences. However, it is not clear operationally we need to consider all such divergences. We establish a simple method for Pinsker…

Information Theory · Computer Science 2025-04-02 Ian George , Alice Zheng , Akshay Bansal

This paper develops an optimal Chernoff type bound for the probabilities of large deviations of sums $\sum_{k=1}^n f (X_k)$ where $f$ is a real-valued function and $(X_k)_{k \in \mathbb{Z}_{\ge 0}}$ is a finite state Markov chain with an…

Probability · Mathematics 2019-12-24 Vrettos Moulos , Venkat Anantharam

The aim of this note is to investigate the concentration properties of unbounded functions of geometrically ergodic Markov chains. We derive concentration properties of centered functions with respect to the square of the Lyapunov's…

Statistics Theory · Mathematics 2016-09-14 Olivier Wintenberger

In this article, relying on Foster-Lyapunov drift conditions, we establish subexponential upper and lower bounds on the rate of convergence in the $\mathrm{L}^p$-Wasserstein distance for a class of irreducible and aperiodic Markov…

Probability · Mathematics 2022-02-28 Ari Arapostathis , Guodong Pang , Nikola Sandrić

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
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