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Let $(\xi_i)_{i=1,...,n}$ be a sequence of independent and symmetric random variables. We consider the upper bounds on tail probabilities of self-normalized deviations $$ \mathbf{P} \Big( \max_{1\leq k \leq n} \sum_{i=1}^{k} |\xi_i|\big/…

Probability · Mathematics 2017-05-05 Xiequan Fan

We develop a general technique for bounding the tail of the total variation distance between the empirical and the true distributions over countable sets. Our methods sharpen a deviation bound of Devroye (1983) for distributions over finite…

Statistics Theory · Mathematics 2012-06-06 Daniel Berend , Aryeh Kontorovich

We prove the first Chernoff-Hoeffding bounds for general nonreversible finite-state Markov chains based on the standard L_1 (variation distance) mixing-time of the chain. Specifically, consider an ergodic Markov chain M and a weight…

Probability · Mathematics 2012-01-31 Kai-Min Chung , Henry Lam , Zhenming Liu , Michael Mitzenmacher

A distributional symmetry is invariance of a distribution under a group of transformations. Exchangeability and stationarity are examples. We explain that a result of ergodic theory provides a law of large numbers: If the group satisfies…

Statistics Theory · Mathematics 2021-11-30 Morgane Austern , Peter Orbanz

Chebyshev's inequality provides an upper bound on the tail probability of a random variable based on its mean and variance. While tight, the inequality has been criticized for only being attained by pathological distributions that abuse the…

Optimization and Control · Mathematics 2020-10-16 Ernst Roos , Ruud Brekelmans , Wouter van Eekelen , Dick den Hertog , Johan van Leeuwaarden

We establish the Level-1 and Level-3 Large Deviation Principles (LDPs) for invariant measures on shift spaces over finite alphabets under very general decoupling conditions for which the thermodynamic formalism does not apply. Such…

Mathematical Physics · Physics 2019-06-28 Noé Cuneo , Vojkan Jakšić , Claude-Alain Pillet , Armen Shirikyan

We discuss ground state factorization schemes in spin $S$ arrays with general $XYZ$ couplings under general magnetic fields, not necessarily uniform or transverse. It is first shown that given arbitrary spin alignment directions at each…

Quantum Physics · Physics 2016-11-02 M. Cerezo , R. Rossignoli , N. Canosa

In this paper non-asymptotic exact exponential estimates are derived for the tail of maximum distribution of random field in the terms of majoring measures or, equally, generic chaining.

Probability · Mathematics 2008-02-05 E. Ostrovsky , E. Rogover

Derandomization of Chernoff bound with union bound is already proven in many papers. We here give another explicit version of it that obtains a construction of size that is arbitrary close to the probabilistic nonconstructive size. We apply…

Discrete Mathematics · Computer Science 2016-08-05 Nader H. Bshouty

Starting with the large deviation principle (LDP) for the Erd\H{o}s-R\'enyi binomial random graph $\mathcal{G}(n,p)$ (edge indicators are i.i.d.), due to Chatterjee and Varadhan (2011), we derive the LDP for the uniform random graph…

Probability · Mathematics 2018-05-01 Amir Dembo , Eyal Lubetzky

We consider "randomized" statistics constructed by using a finite number of observations a random field at randomly chosen points. We generalize the invariance principle (the functional CLT), the Glivenko--Cantelli theorem, the theorem…

Probability · Mathematics 2022-07-19 Youri Davydov , Arkady Tempelman

We apply the recent results of F. Hiai, M. Mosonyi and T. Ogawa [arXiv:0707.2020, to appear in J. Math. Phys.] to the asymptotic hypothesis testing problem of locally faithful shift-invariant quasi-free states on a CAR algebra. We use a…

Quantum Physics · Physics 2009-11-13 M. Mosonyi , F. Hiai , T. Ogawa , M. Fannes

We establish a large deviation principle (LDP) for probability graphons, which are symmetric functions from the unit square into the space of probability measures. This notion extends classical graphons and provides a flexible framework for…

Probability · Mathematics 2025-09-18 Pierfrancesco Dionigi , Giulio Zucal

We present a new large-deviation approach to investigate the critical properties of the Anderson model on the Bethe lattice close to the localization transition in the thermodynamic limit. Our method allows us to study accurately the…

Disordered Systems and Neural Networks · Physics 2022-09-01 Giulio Biroli , Alexander K. Hartmann , Marco Tarzia

Motivated by the recent discovery of a quantum Chernoff theorem for asymptotic state discrimination, we investigate the distinguishability of two bipartite mixed states under the constraint of local operations and classical communication…

Quantum Physics · Physics 2011-03-16 William Matthews , Andreas Winter

Laws of large numbers, starting from certain nonequilibrium measures, have been shown for the integrated current across a bond, and a tagged particle in one-dimensional symmetric nearest-neighbor simple exclusion [Ann. Inst. Henri Poincare…

Probability · Mathematics 2013-05-28 Sunder Sethuraman , S. R. S. Varadhan

For H\"older continuous functions $f_i$, $i=0,\ldots ,d$, on a subshift of finite type and $\Theta\subset \mathbb \R^d$ we consider a parametrized family of potentials $\{F_\theta= f_0+\sum_{i=1}^d \theta_i f_i : \theta\in \Theta\}$. We…

Dynamical Systems · Mathematics 2024-08-05 Manfred Denker , Marc Keßeböhmer , Artur O. Lopes , Silvia R. C. Lopes

We consider a general system of n noninteracting identical particles which evolve under a given dynamical law and whose initial microstates are a priori independent. The time evolution of the n-particle average of a bounded function on the…

chao-dyn · Physics 2021-04-28 Brian R. La Cour , William C. Schieve

We explore some properties of the conditional distribution of an i.i.d. sample under large exceedances of its sum. Thresholds for the asymptotic independance of the summands are observed, in contrast with the classical case when the…

Statistics Theory · Mathematics 2016-10-14 Maeva Biret , Michel Broniatowski , Zangsheng Cao

A survey is given of some Chernoff type bounds for the tail probabilities P(X-EX > a) and P(X-EX < a) when X is a random variable that can be written as a sum of indicator variables that are either independent or negatively related. Most…

Probability · Mathematics 2016-09-05 Svante Janson