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The problem is sequence prediction in the following setting. A sequence x1,..., xn,... of discrete-valued observations is generated according to some unknown probabilistic law (measure) mu. After observing each outcome, it is required to…

Machine Learning · Computer Science 2015-10-19 Daniil Ryabko

This paper concerns the approximation of probability measures on $\mathbf{R}^d$ with respect to the Kullback-Leibler divergence. Given an admissible target measure, we show the existence of the best approximation, with respect to this…

Probability · Mathematics 2017-06-26 Yulong Lu , Andrew M. Stuart , Hendrik Weber

We present a simple criterion, only based on second moment assumptions, for the convergence of polynomial or Wiener chaos to a Gaussian limit. We exploit this criterion to obtain new Gaussian asymptotics for the partition functions of…

Probability · Mathematics 2022-10-07 Francesco Caravenna , Francesca Cottini

We determine the exact threshold of the extended Seiberg bound for the existence of correlation functions in the boundary Liouville conformal field theory in the unit disk. In probabilistic terms, our result is a toolbox yielding the…

Probability · Mathematics 2023-02-14 Yichao Huang

In this paper, we study the singularly perturbed Gaussian unitary ensembles defined by the measure \begin{equation*} \frac{1}{C_n} e^{- n\textrm{tr}\, V(M;\lambda,\vec{t}\;)}dM, \end{equation*} over the space of $n \times n$ Hermitian…

Mathematical Physics · Physics 2019-10-23 Dan Dai , Shuai-Xia Xu , Lun Zhang

This paper establishes the theoretical foundations for the asymptotic separability of Gaussian Mixture Models (GMMs) in high dimensions by extending the classical Feldman-H\'ajek theorem. We first prove that a countable mixture of Gaussian…

Statistics Theory · Mathematics 2026-01-13 Umberto Michelucci

Multifractal systems usually have singularity spectra defined on bounded sets of H\"older exponents. As a consequence, their associated multifractal scaling exponents are expected to depend linearly upon statistical moment orders at high…

Fluid Dynamics · Physics 2021-06-30 L. Moriconi

Let $E$ be a Moran set on $\mathbb{R}^1$ associated with a closed interval $J$ and two sequences $(n_k)_{k=1}^\infty$ and $(\mathcal{C}_k=(c_{k,j})_{j=1}^{n_k})_{k\geq1}$. Let $\mu$ be the infinite product measure (Moran measure) on $E$…

Functional Analysis · Mathematics 2018-02-13 Sanguo Zhu

The Collective Graphical Model (CGM) models a population of independent and identically distributed individuals when only collective statistics (i.e., counts of individuals) are observed. Exact inference in CGMs is intractable, and previous…

Machine Learning · Computer Science 2014-05-21 Li-Ping Liu , Daniel Sheldon , Thomas G. Dietterich

Many low temperature disordered systems are expected to exhibit Poisson-Dirichlet (PD) statistics. In this paper, we focus on the case when the underlying disorder is a logarithmically correlated Gaussian process $\phi_N$ on the box…

Probability · Mathematics 2023-02-15 Shirshendu Ganguly , Kyeongsik Nam

We try to design a simple model exhibiting self-organized criticality, which is amenable to a rigorous mathematical analysis. To this end, we modify the generalized Ising Curie-Weiss model by implementing an automatic control of the inverse…

Probability · Mathematics 2013-06-10 Matthias Gorny

Selberg and Morris integral probability distributions are long conjectured to be distributions of the total mass of the Bacry-Muzy Gaussian Multiplicative Chaos measures with non-random logarithmic potentials on the unit interval and…

Probability · Mathematics 2018-10-30 Dmitry Ostrovsky

We study the question, ``For which reals $x$ does there exist a measure $\mu$ such that $x$ is random relative to $\mu$?'' We show that for every nonrecursive $x$, there is a measure which makes $x$ random without concentrating on $x$. We…

Logic · Mathematics 2007-07-11 Jan Reimann , Theodore Slaman

In this paper we study algorithms to find a Gaussian approximation to a target measure defined on a Hilbert space of functions; the target measure itself is defined via its density with respect to a reference Gaussian measure. We employ the…

Numerical Analysis · Mathematics 2014-08-11 Frank J. Pinski , Gideon Simpson , Andrew M. Stuart , Hendrik Weber

Let $A \subset \mathbb{R}^d$, $d\ge 2$, be a compact convex set and let $\mu = \varrho_0 dx$ be a probability measure on $A$ equivalent to the restriction of Lebesgue measure. Let $\nu = \varrho_1 dx$ be a probability measure on $B_r :=…

Differential Geometry · Mathematics 2008-05-12 Vladimir I. Bogachev , Alexander V. Kolesnikov

This work considers the computation of risk measures for quantities of interest governed by PDEs with Gaussian random field parameters using Taylor approximations. While efficient, Taylor approximations are local to the point of expansion,…

Numerical Analysis · Mathematics 2024-08-14 Dingcheng Luo , Joshua Chen , Peng Chen , Omar Ghattas

In complex and unknown processes, global models are initially generated over the entire experimental space but often fail to provide accurate predictions in local areas. A common approach is to use local models, which requires partitioning…

Machine Learning · Computer Science 2025-05-29 Dominik Polke , Tim Kösters , Elmar Ahle , Dirk Söffker

We obtain optimal Gaussian concentration bounds (GCBs) for stochastic chains of unbounded memory (SCUMs) on countable alphabets. These stochastic processes are also known as "chains with complete connections" or "$g$-measures". We consider…

Probability · Mathematics 2020-03-24 J. -R. Chazottes , S. Gallo , D. Takahashi

For a pair of coupled rectangular random matrices we consider the squared singular values of their product, which form a determinantal point process. We show that the limiting mean distribution of these squared singular values is described…

Mathematical Physics · Physics 2020-06-24 Guilherme L. F. Silva , Lun Zhang

Let g(x)=x/2 + 17/30 (mod 1), let \xi_i, i= 1,2,... be a sequence of independent, identically distributed random variables with uniform distribution on the interval [0,1/15], define g_i(x)=g(x)+ \xi_i (mod 1) and, for n=1,2,..., define…

Probability · Mathematics 2016-06-03 Thomas Kaijser
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