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In this paper, we study inference for high-dimensional data characterized by small sample sizes relative to the dimension of the data. In particular, we provide an infinite-dimensional framework to study statistical models that involve…

Statistics Theory · Mathematics 2010-02-25 Jim Kuelbs , Anand N. Vidyashankar

Distance correlation has become an increasingly popular tool for detecting the nonlinear dependence between a pair of potentially high-dimensional random vectors. Most existing works have explored its asymptotic distributions under the null…

Statistics Theory · Mathematics 2021-10-06 Lan Gao , Yingying Fan , Jinchi Lv , Qi-Man Shao

Sample correlation matrices are employed ubiquitously in statistics. However, quite surprisingly, little is known about their asymptotic spectral properties for high-dimensional data, particularly beyond the case of "null models" for which…

Statistics Theory · Mathematics 2019-03-13 David Morales-Jimenez , Iain M. Johnstone , Matthew R. McKay , Jeha Yang

We reassess the relation between classical lattice dimer models and the continuum elastic description of a lattice of fluctuating polymers. In the absence of randomness we determine the density and line tension of the polymers in terms of…

Statistical Mechanics · Physics 2015-06-25 Ying Jiang , Thorsten Emig

We study the supremum of some random Dirichlet polynomials with independent coefficients and obtain sharp upper and lower bounds for supremum expectation thus extending the results from our previous work (see…

Probability · Mathematics 2009-04-23 Mikhail Lifshits , Michel Weber

I discuss models for a continuum directed random polymer in a disordered environment in which the polymer lives on a fractal called the \textit{diamond hierarchical lattice}, a self-similar metric space forming a network of interweaving…

Probability · Mathematics 2019-07-12 Jeremy Clark

High-dimensional data sets are commonly collected in many contemporary applications arising in various fields of scientific research. We present two views of finite samples in high dimensions: a probabilistic one and a nonprobabilistic one.…

Statistics Theory · Mathematics 2013-11-13 Jinchi Lv

The explicit expression for the the probability distribution function of the endpoint fluctuations of one-dimensional directed polymers in random potential is derived in terms of the Bethe ansatz replica technique by mapping the replicated…

Statistical Mechanics · Physics 2015-06-11 Victor Dotsenko

Central limit theorems for the log-volume of a class of random convex bodies in $\mathbb{R}^n$ are obtained in the high-dimensional regime, that is, as $n\to\infty$. In particular, the case of random simplices pinned at the origin and…

It is a well-known open problem in the literature on random polymers to show that a directed polymer in random environment localizes around a favorite path at low temperature. A precise statement of this conjecture is formulated and proved…

Probability · Mathematics 2019-09-04 Sourav Chatterjee

It is shown that when $d\ge 3$, the growing random surface generated by the $(d+1)$-dimensional directed polymer model at sufficiently high temperature, after being smoothed by taking microscopic local averages, converges to a solution of…

Probability · Mathematics 2022-05-16 Sourav Chatterjee

We consider a model of directed polymers on regular trees with complex-valued random weights introduced by Cook and Derrida [CD90] and studied mathematically by Derrida, Evans and Speer [DES93]. In addition to the usual weak-disorder and…

Probability · Mathematics 2023-10-04 Leonardo Medina-Espinosa , Gregorio R. Moreno Flores

The overlap of a $d+1$ dimensional directed polymer of length $t$ in a random medium is studied using a Renormalization Group approach. In $d>2$ it vanishes at $T_c$ for $t\rightarrow \infty$ as $t^{\Sigma}$ where…

Condensed Matter · Physics 2009-10-22 Sutapa Mukherji

We study the behavior of the elastic polymer, a model of a directed polymer in a continuous Gaussian random environment that is independent in time and correlated in space, as the dimension of the environment is taken to infinity. We give…

Probability · Mathematics 2026-05-08 Gerard Ben Arous , Pax Kivimae

Directed acyclic graphs are widely used to describe the causal effects among random variables, and the inference of those causal effects has become an popular topic in statistics and machine learning, and has wide applications in…

Methodology · Statistics 2025-06-24 Chen Shuyan , Liu Xin , Wang Shaoli

Denoising Diffusion Probabilistic Models (DDPM) are powerful state-of-the-art methods used to generate synthetic data from high-dimensional data distributions and are widely used for image, audio, and video generation as well as many more…

Machine Learning · Statistics 2025-04-25 Iskander Azangulov , George Deligiannidis , Judith Rousseau

We construct a phenomenological theory of self-localization of directed polymers in d+1 dimensions. In d=1 we show that the polymer is always self-localized, whereas in d=2 there is a phase transition between localized and free states. We…

Statistical Mechanics · Physics 2007-05-23 T. J. Newman , Eugene B. Kolomeisky

In these lecture notes, which are based on the mini-course given at 2013 Prague School on Mathematical Statistical Physics, we discuss ballistic phase of quenched and annealed stretched polymers in random environment on ${\mathbb Z}^d$ with…

Probability · Mathematics 2014-12-02 Dmitry Ioffe

In some estimation problems, especially in applications dealing with information theory, signal processing and biology, theory provides us with additional information allowing us to restrict the parameter space to a finite number of points.…

Methodology · Statistics 2012-07-25 Christine Choirat , Raffaello Seri

Imaging through scattering and random media is an outstanding problem that to date has been tackled by either measuring the medium transmission matrix or exploiting linear correlations in the transmitted speckle patterns. However,…

Optics · Physics 2022-04-07 Ilya Starshynov , Alex Turpin , Philip Binner , Daniele Faccio