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In probability theory and statistics, the IID model represents a single population, and a large, potentially infinite sample from this population. Main theorems, in particular the central limit theorem and laws of large number (LLN) assure…

Statistics Theory · Mathematics 2017-10-02 Uwe Saint-Mont

We consider high-dimensional estimation problems where the number of parameters diverges with the sample size. General conditions are established for consistency, uniqueness, and asymptotic normality in both unpenalized and penalized…

Statistics Theory · Mathematics 2025-04-08 Jana Gauss , Thomas Nagler

We prove the uniform in space and time convergence of the scaled heights of large classes of deterministic growth models that are monotone and equivariant under translations by constants. The limits are characterized as the unique…

Probability · Mathematics 2022-06-29 Sourav Chatterjee , Panagiotis E. Souganidis

We find the symmetry generators for the Friedman equations emanating from a perfect fluid source, in the presence of a cosmological constant term. The relevant dynamics is seen to be governed by two coupled, first order ordinary…

General Relativity and Quantum Cosmology · Physics 2020-09-23 T. Pailas , N. Dimakis , Andronikos Paliathanasis , Petros A. Terzis , T. Christodoulakis

Dynamical systems theory is especially well-suited for determining the possible asymptotic states (at both early and late times) of cosmological models, particularly when the governing equations are a finite system of autonomous ordinary…

General Relativity and Quantum Cosmology · Physics 2007-05-23 A. A. Coley

This paper deals with the stabilization of a class of linear infinite-dimensional systems with unbounded control operators and subject to a boundary disturbance. We assume that there exists a linear feedback law that makes the origin of the…

Analysis of PDEs · Mathematics 2022-10-26 Ismaïla Balogoun , Swann Marx , Franck Plestan

We give general theorems on asymptotic normality for additive functionals of random tries generated by a sequence of independent strings. These theorems are applied to show asymptotic normality of the distribution of random fringe trees in…

Probability · Mathematics 2020-03-06 Svante Janson

A two-dimensional threshold function of k-valued logic can be viewed as coloring of the points of a k x k square lattice into two colors such that there exists a straight line separating points of different colors. For the number of such…

Combinatorics · Mathematics 2010-12-09 Max A. Alekseyev

We present a novel distribution-free approach, the data-driven threshold machine (DTM), for a fundamental problem at the core of many learning tasks: choose a threshold for a given pre-specified level that bounds the tail probability of the…

Machine Learning · Computer Science 2016-10-17 Shuang Li , Yao Xie , Le Song

This paper presents a theory of skiplists of arbitrary height, and shows decidability of the satisfiability problem for quantifier-free formulas. A skiplist is an imperative software data structure that implements sets by maintaining…

Logic in Computer Science · Computer Science 2013-01-21 César Sánchez , Alejandro Sánchez

Linear thresholding models postulate that the conditional distribution of a response variable in terms of covariates differs on the two sides of a (typically unknown) hyperplane in the covariate space. A key goal in such models is to learn…

Statistics Theory · Mathematics 2021-10-01 Debarghya Mukherjee , Moulinath Banerjee , Debasri Mukherjee , Ya'acov Ritov

It has recently been shown that Skyrmions with a fixed size can exist in theories without a Skyrme term, providing the Skyrmion is located on a domain wall. Here we numerically compute domain wall Skyrmions of this type, in a…

High Energy Physics - Theory · Physics 2015-06-15 Paul Jennings , Paul Sutcliffe

Eternal domination is a dynamic process by which a graph is protected from an infinite sequence of vertex intrusions. In eternal distance-$k$ domination, guards initially occupy the vertices of a distance-$k$ dominating set. After a vertex…

Combinatorics · Mathematics 2022-11-21 Danielle Cox , Erin Meger , M. E. Messinger

We determine the probability thresholds for the existence of monotone paths, of finite and infinite length, in random oriented graphs with vertex set $\mathbb N^{[k]}$, the set of all increasing $k$-tuples in $\mathbb N$. These graphs…

Probability · Mathematics 2016-10-05 Pietro Majer , Matteo Novaga

The aim of this note is to state a couple of general results about the properties of the penalized maximum likelihood estimators (pMLE) and of the posterior distribution for parametric models in a non-asymptotic setup and for possibly large…

Statistics Theory · Mathematics 2022-12-13 Vladimir Spokoiny

We examine the properties of the scale invariant cosmological models, also making the specific hypothesis of the scale invariance of the empty space at large scales. Numerical integrations of the cosmological equations for different values…

General Relativity and Quantum Cosmology · Physics 2016-05-25 Andre Maeder

We study the nonlinear realization of supersymmetry in a dynamical/cosmological background in which derivative terms like kinetic terms are finite. Starting from linearly realized theories, we integrate out heavy modes without neglecting…

High Energy Physics - Theory · Physics 2022-02-24 Shuntaro Aoki , Takahiro Terada

Let $X$ be an arbitrary smooth hypersurface in $\mathbb{C} \mathbb{P}^n$ of degree $d$. We prove the de Jong-Debarre Conjecture for $n \geq 2d-4$: the space of lines in $X$ has dimension $2n-d-3$. We also prove an analogous result for…

Algebraic Geometry · Mathematics 2020-10-15 Roya Beheshti , Eric Riedl

The solutions to surface evolution problems like mean curvature flow can be expressed as value functions of suitable stochastic control problems, obtained as limit of a family of regularised control problems. The control-theoretical…

Analysis of PDEs · Mathematics 2020-05-22 Nicolas Dirr , Federica Dragoni , Raffaele Grande

Sampling is a fundamental problem in computer science and statistics. However, for a given task and stream, it is often not possible to choose good sampling probabilities in advance. We derive a general framework for adaptively changing the…

Machine Learning · Statistics 2022-06-16 Daniel Ting