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We study a model of spatial random permutations over a discrete set of points. Formally, a permutation $\sigma$ is sampled proportionally to the weight $\exp\{-\alpha \sum_x V(\sigma(x)-x)\},$ where $\alpha>0$ is the temperature and $V$ is…

Probability · Mathematics 2019-04-09 Inés Armendáriz , Pablo A. Ferrari , Nicolás Frevenza

Power law or generalized polynomial regressions with unknown real-valued exponents and coefficients, and weakly dependent errors, are considered for observations over time, space or space--time. Consistency and asymptotic normality of…

Statistics Theory · Mathematics 2012-05-14 Peter M. Robinson

For a subshift $(X, \sigma_X)$ and a subadditive sequence $\mathcal{F}=\{\log f_n\}_{n=1}^{\infty}$ on $X$, we study equivalent conditions for the existence of $h\in C(X)$ such that $\lim_{n\rightarrow\infty}(1/{n})\int \log f_n d \mu=\int…

Dynamical Systems · Mathematics 2021-10-05 Yuki Yayama

This survey paper is based on a talk given at the 44th Summer Symposium in Real Analysis in Paris. This line of research was initiated by a question of Haight and Weizs\"aker concerning almost everywhere convergence properties of series of…

Classical Analysis and ODEs · Mathematics 2022-09-27 Zoltán Buczolich

We establish general versions of a variety of results for quasiconvex, lower-semicontinuous, and law-invariant functionals. Our results extend well-known results from the literature to a large class of spaces of random variables. We…

Pricing of Securities · Quantitative Finance 2021-01-21 Fabio Bellini , Pablo Koch-Medina , Cosimo Munari , Gregor Svindland

We study inductive bias in Transformers in the infinitely over-parameterized Gaussian process limit and argue transformers tend to be biased towards more permutation symmetric functions in sequence space. We show that the representation…

Machine Learning · Computer Science 2024-05-29 Itay Lavie , Guy Gur-Ari , Zohar Ringel

In this paper, we propose a method for transferring feature representation to lightweight student models from larger teacher models. We mathematically define a new notion called \textit{perception coherence}. Based on this notion, we…

Machine Learning · Statistics 2026-02-24 Hai-Vy Nguyen , Fabrice Gamboa , Sixin Zhang , Reda Chhaibi , Serge Gratton , Thierry Giaccone

Finding self-similarity is a key step for understanding the governing law behind complex physical phenomena. Traditional methods for identifying self-similarity often rely on specific models, which can introduce significant bias. In this…

Soft Condensed Matter · Physics 2025-02-05 Ryota Watanabe , Takanori Ishii , Yuji Hirono , Hirokazu Maruoka

We show how, based on considerations on the observed form of the galaxy 2-point spatial correlation function xi(r), a very simplified -- yet surprisingly effective -- model for the linear density fluctuations power spectrum can be…

Astrophysics · Physics 2009-10-22 Enzo Branchini , Luigi Guzzo , Riccardo Valdarnini

The compatibility between the de Sitter Swampland conjecture and Ho\v{r}ava--Lifshitz $F(\bar{R})$ theories with a flat FLRW metric is studied. We first study the standard $f(R)$ theories and show that the only way in which the dS…

General Relativity and Quantum Cosmology · Physics 2023-11-02 H. Garcia-Compean , D. Mata-Pacheco , L. Zapata

The dispersion relation of de Sitter special relativity is obtained in a simple and compact form, which is formally similar to the dispersion relation of ordinary special relativity. It is manifestly invariant under change of scale of mass,…

General Relativity and Quantum Cosmology · Physics 2015-03-19 J. P. Beltran Almeida , C. S. O. Mayor , J. G. Pereira

Consider a measure $\mu_\lambda = \sum_x \xi_x \delta_x$ where the sum is over points $x$ of a Poisson point process of intensity $\lambda$ on a bounded region in $d$-space, and $\xi_x$ is a functional determined by the Poisson points near…

Probability · Mathematics 2013-02-05 Mathew D. Penrose , Andrew R. Wade

There is a wide range of applications where the local extrema of a function are the key quantity of interest. However, there is surprisingly little work on methods to infer local extrema with uncertainty quantification in the presence of…

Methodology · Statistics 2023-09-28 Meng Li , Zejian Liu , Cheng-Han Yu , Marina Vannucci

A common method for assessing validity of Bayesian sampling or approximate inference methods makes use of simulated data replicates for parameters drawn from the prior. Under continuity assumptions, quantiles of functions of the simulated…

Computation · Statistics 2019-11-21 Xuejun Yu , David J. Nott , Minh-Ngoc Tran , Nadja Klein

It is a little known fact that while he was developing his theory of general relativity, Einstein's initial idea was a variable speed of light theory. Indeed space-time curvature can be mimicked by a speed of light $c(r)$ that depends on…

General Physics · Physics 2015-03-31 Alexander Unzicker , Jan Preuss

We study spectral densities for systems on lattices, which, at a phase transition display, power-law spatial correlations. Constructing the spatial correlation matrix we prove that its eigenvalue density shows a power law that can be…

Mathematical Physics · Physics 2014-11-24 Vinayak , T. Prosen , B. Buca , T. H. Seligman

When data analysts train a classifier and check if its accuracy is significantly different from chance, they are implicitly performing a two-sample test. We investigate the statistical properties of this flexible approach in the…

Machine Learning · Computer Science 2020-02-18 Ilmun Kim , Aaditya Ramdas , Aarti Singh , Larry Wasserman

We propose a general formalism of iterated random functions with semigroup property, under which exact and approximate Bayesian posterior updates can be viewed as specific instances. A convergence theory for iterated random functions is…

Machine Learning · Statistics 2013-11-05 Arash A. Amini , XuanLong Nguyen

We consider random walk among iid, uniformly elliptic conductances on $\mathbb Z^d$, and prove the Einstein relation (see Theorem 1). It says that the derivative of the velocity of a biased walk as a function of the bias equals the…

Probability · Mathematics 2015-12-08 Nina Gantert , Xiaoqin Guo , Jan Nagel

Karamata's integral representation for slowly varying functions is extended to a broader class of the so-called $\psi$-locally constant functions, i.e. functions $f(x)>0$ having the property that, for a given non-decreasing function $\psi…

Probability · Mathematics 2010-06-17 A. A. Borovkov , K. A. Borovkov
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