Searcharxiv⌕ Search

arXiv subjects

Witold Bednorz

Publications and source records attributed to Witold Bednorz.

36 records · Page 2Linked to original sources
arXiv2016

Some remarks on the Oleszkiewicz problem

In this paper we study the question how to easily verify that the expectation of the supremum of a one canonical Bernoulli process dominates the same quantity for another process of this type. In the setting of Gaussian canonical processes it is known that such a comparison holds for contractions in the Euclidean distance. We do state and prove a similar result for Bernoulli processes. In particular we get a partial answer to the Oleszkiewicz conjecture about the comparability of weak and strong moments for type Bernoulli series in a Banach space.

math.PR↗
arXiv2016

Bounds for stochastic processes on product index spaces

In this paper we discuss the question how to bound supremum of a stochastic process with the index set of a product type. There is a tempting idea to approach the question by the analysis of the process on each of the marginal index spaces separately. However it turns out that we also need to study suitable partitions of the whole index space. We show what can be done in this direction and how to use the method to reprove some known results. In particular we observe that all known applications of the Bernoulli Theorem can be obtained in this way, moreover we use the shattering dimension to slightly extend the application to VC classes. We also show some application to the regularity of paths for processes which take values in vector spaces. Finally we give a short proof of the Mendelson-Paouris result on sums of squares for empirical processes.

math.PR↗
arXiv2015

Moment estimates implied by modified log-Sobolev inequalities

We study a class of logarithmic Sobolev inequalities with a general form of the energy functional. The class generalizes various examples of modified logarithmic Sobolev inequalities considered previously in the literature. Refining a method of Aida and Stroock for the classical logarithmic Sobolev inequality, we prove that if a measure on $\mathbb{R}^n$ satisfies a modified logarithmic Sobolev inequality then it satisfies a family of $L^p$-Sobolev-type inequalities with non-Euclidean norms of gradients (and dimension-independent constants). The latter are shown to yield various concentration-type estimates for deviations of smooth (not necessarily Lipschitz) functions and measures of enlargements of sets corresponding to non-Euclidean norms. We also prove a two-level concentration result for functions of bounded Hessian and measures satisfying the classical logarithmic Sobolev inequality.

math.PR↗
arXiv2015

Some remarks on MCMC estimation of spectra of integral operators

We prove a law of large numbers for empirical approximations of the spectrum of a kernel integral operator by the spectrum of random matrices based on a sample drawn from a Markov chain, which complements the results by V. Koltchinskii and E. Giné for i.i.d. sequences. In a special case of Mercer's kernels and geometrically ergodic chains, we also provide exponential inequalities, quantifying the speed of convergence.

math.PR↗
arXiv2014

Concentration via chaining method and its applications

In this paper we study the regularity of paths in terms of properties of admissible nets. We show the right concentration inequality above the modulus of continuity. Using the approach we prove the Bernstein type inequality for the empirical processes. Therefore we obtain the best form of concentration for processes studied recently by Mendelson and Paouris. Results of this type are of importance in the compressed sensing theory.

math.PR↗
arXiv2014

Some remarks on the Sudakov minoration

In this paper we discuss Sudakov type minoration for the dependent setting. Sudakov minoration is a well known property first proved for centered Gaussian processes which states that for well separated points there is a natural lower bound on the expectation of the supremum of such a process. We generalize this concept for the dependent setting where we consider log concave random variables and then discuss methods of proving the property.

math.PR↗
arXiv2014

Testing locality and noncontextuality with the lowest moments

The quest for fundamental test of quantum mechanics is an ongoing effort. We here address the question of what are the lowest possible moments needed to prove quantum nonlocality and noncontextuality without any further assumption -- in particular without the often assumed dichotomy. We first show that second order correlations can always be explained by a classical noncontextual local-hidden-variable theory. Similar third-order correlations also cannot violate classical inequalities in general, except for a special state-dependent noncontextuality. However, we show that fourth-order correlations can violate locality and state-independent noncontextuality. Finally we obtain a fourth-order continuous-variable Bell inequality for position and momentum, which can be violated and might be useful in Bell tests closing all loopholes simultaneously.

quant-ph↗
arXiv2013

Exponential Concentration Inequalities for Additive Functionals of Markov Chains

Using the renewal approach we prove exponential inequalities for additive functionals and empirical processes of ergodic Markov chains, thus obtaining counterparts of inequalities for sums of independent random variables. The inequalities do not require functions of the chain to be bounded and moreover all the involved constants are given by explicit formulas whenever the usual drift condition holds, which may be of interest in practical applications e.g. to MCMC algorithms.

math.PR↗
arXiv2013

On the boundedness of Bernoulli processes

We present a positive solution to the so-called Bernoulli Conjecture concerning the characterization of sample boundedness of Bernoulli processes. We also discuss some applications and related open problems.

math.PR↗
arXiv2013

The complete characterization of a.s. convergence of orthogonal series

In this paper we prove the complete characterization of a.s. convergence of orthogonal series in terms of existence of a majorizing measure. It means that for a given $(a_n)^{\infty}_{n=1}$, $a_n>0$, series $\sum^{\infty}_{n=1}a_nφ_n$ is a.e. convergent for each orthonormal sequence $(φ_n)^{\infty}_{n=1}$ if and only if there exists a measure $m$ on \[T=\{0\}\cup\Biggl\{\sum^m_{n=1}a_n^2,m\geq 1\Biggr\}\] such that \[\sup_{t\in T}\int^{\sqrt{D(T)}}_0(m(B(t,r^2)))^{-{1}/{2}}\,dr<\infty,\] where $D(T)=\sup_{s,t\in T}|s-t|$ and $B(t,r)=\{s\in T:|s-t|\leq r\}$. The presented approach is based on weakly majorizing measures and a certain partitioning scheme.

math.PR↗
arXiv2013

The Kendall's Theorem and its Application to the Geometric Ergodicity of Markov Chains

In this paper we prove a sharp quantitative version of the Kendall's Theorem. The Kendal Theorem states that under some mild conditions imposed on a probability distribution on positive integers (i.e. probabilistic sequence) one can prove convergence of its renewal sequence. Due to the well-known property - the first entrance last exit decomposition - such results are of interest in the stability theory of time homogeneous Markov chains. In particular the approach may be used to measure rates of convergence of geometrically ergodic Markov chains and consequently implies estimates on convergence of MCMC estimators.

math.PR↗
arXiv2012

The majorizing measure approach to the sample boundedness

In this paper we describe the alternative approach to the sample boundedness and continuity of stochastic processes. We show that the regularity of paths can be understood in terms of a distribution of the argument maximum. For a centered Gaussian process X(t), t\in T we obtain a short proof of the exact lower bound on E\sup_{t\in T} X(t). Finally we prove the equivalence of a usual majorizing measure functional to its conjugate version.

math.PR↗
arXiv2012

Orlicz integrability of additive functionals of Harris ergodic Markov chains

For a Harris ergodic Markov chain $(X_n)_{n\ge 0}$, on a general state space, started from the so called small measure or from the stationary distribution we provide optimal estimates for Orlicz norms of sums $\sum_{i=0}^τf(X_i)$, where $τ$ is the first regeneration time of the chain. The estimates are expressed in terms of other Orlicz norms of the function $f$ (wrt the stationary distribution) and the regeneration time $τ$ (wrt the small measure). We provide applications to tail estimates for additive functionals of the chain $(X_n)$ generated by unbounded functions as well as to classical limit theorems (CLT, LIL, Berry-Esseen).

math.PR↗
arXiv2007

H{ö}lder continuity of random processes

The paper will be published in JOTP. In the paper we prove Holder Continuity for ceratian classes of processes with bounded increments. The paper generalizes results obtained by Kwapien and Rosinski in Sample H{ö}lder continuity of stochastic processes and majorizing measures. \textit{Seminar on Stochastic Analysis, Random Fields and Applications IV, Progr. in Probab.} {\bf 58}, 155--163. Birkh{ä}user, Basel.

math.PR↗
arXiv2007

On a type Sobolev inequality and its applications

In the paper we pursue the analysis from the section 5 of the Talagrand's paper "Sample boundedness of stochastic processes under increment conditions." Ann. Probab. 18, No. 1, 1-49. In particular we give the proof of some Sobolev Inequality and then apply it to obtain if and only if condition for all processes with bounded icrements to have bounded samples. The processes are defined on a compact, concave subspaces of $\R^n$ with a metric $d(s,t)=η(||s-t||)$, where $η$ is concave and $||.||$ is a norm on $\R^n$.

math.PR↗
arXiv2006

A theorem on majorizing measures

Let $(T,d)$ be a metric space and $ϕ:\mathbb{R}_+\to \mathbb{R}$ an increasing, convex function with $ϕ(0)=0$. We prove that if $m$ is a probability measure $m$ on $T$ which is majorizing with respect to $d,ϕ$, that is, $\mathcal{S}:=\sup_{x\in T}\int^{D(T)}_0ϕ^{-1}(\frac{1}{m(B(x,ε))}) dε<\infty$, then \[\mathbf{E}\sup_{s,t\in T}|X(s)-X(t)|\leq 32\mathcal{S}\] for each separable stochastic process $X(t)$, $t\in T$, which satisfies $\mathbf{E}ϕ(\frac{|X(s)-X(t)|}{d(s,t)})\leq 1$ for all $s,t\in T$, $s\neq t$. This is a strengthening of one of the main results from Talagrand [Ann. Probab. 18 (1990) 1--49], and its proof is significantly simpler.

math.PR↗