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In this paper, we propose and study neural network based methods for solutions of high-dimensional quadratic porous medium equation (QPME). Three variational formulations of this nonlinear PDE are presented: a strong formulation and two…

Numerical Analysis · Mathematics 2022-05-09 Jianfeng Lu , Min Wang

We study a parametric class of isotropic but not necessarily stationary Poisson hyperplane tessellations in n-dimensional Euclidean space. Our focus is on the volume of the zero cell, i.e. the cell containing the origin. As a main result,…

Probability · Mathematics 2012-11-16 Julia Hoerrmann , Daniel Hug

For enumerative problems, i.e. computable functions f from N to Z, we define the notion of an effective (or closed) formula. It is an algorithm computing f(n) in the number of steps that is polynomial in the combined size of the input n and…

Combinatorics · Mathematics 2018-09-11 Martin Klazar

A new initialization method for hidden parameters in a neural network is proposed. Derived from the integral representation of the neural network, a nonparametric probability distribution of hidden parameters is introduced. In this…

Machine Learning · Computer Science 2014-02-20 Sho Sonoda , Noboru Murata

It has been shown that the maximum stable set problem in some infinite graphs, and the kissing number problem in particular, reduces to a minimization problem over the cone of copositive kernels. Optimizing over this infinite dimensional…

Optimization and Control · Mathematics 2018-12-04 Olga Kuryatnikova , Juan C. Vera

This paper studies and critically discusses the construction of nonparametric confidence regions for density level sets. Methodologies based on both vertical variation and horizontal variation are considered. The investigations provide…

Statistics Theory · Mathematics 2019-03-05 Wanli Qiao , Wolfgang Polonik

We study geometric variations of the discriminating code problem. In the \emph{discrete version} of the problem, a finite set of points $P$ and a finite set of objects $S$ are given in $\mathbb{R}^d$. The objective is to choose a subset…

Computational Geometry · Computer Science 2023-06-30 Sanjana Dey , Florent Foucaud , Subhas C Nandy , Arunabha Sen

A density estimation method in a Bayesian nonparametric framework is presented when recorded data are not coming directly from the distribution of interest, but from a length biased version. From a Bayesian perspective, efforts to…

Statistics Theory · Mathematics 2015-10-23 Spyridon J. Hatjispyros , Theodoros Nicoleris , Stephen G. Walker

Given an open, bounded, planar set $\Omega$, we consider its $p$-Cheeger sets and its isoperimetric sets. We study the set-valued map $\mathfrak{V}:[\frac12,+\infty)\rightarrow\mathcal{P}((0,|\Omega|])$ associating to each $p$ the set of…

Analysis of PDEs · Mathematics 2023-02-13 Marco Caroccia , Giorgio Saracco

Let $\{U_n\}_{n \geqslant 0}$ and $\{G_m\}_{m \geqslant 0}$ be two linear recurrence sequences defined over the integers. We establish an asymptotic formula for the number of integers $c$ in the range $[-x, x]$ which can be represented as…

Number Theory · Mathematics 2020-06-18 Daodao Yang

The main aim of this paper is to provide a method which allows finding limiting shapes of symbolic generic initial systems of higher-dimensional subvarieties of P^n. M. Mustata and S. Mayes established a connection between volumes of…

Algebraic Geometry · Mathematics 2014-07-03 Marcin Dumnicki , Justyna Szpond , Halszka Tutaj-Gasinska

Nonparametric estimation of a mixing density based on observations from the corresponding mixture is a challenging statistical problem. This paper surveys the literature on a fast, recursive estimator based on the predictive recursion…

Methodology · Statistics 2022-09-15 Ryan Martin

The main contributions of this paper are the proposition and the convergence analysis of a class of inertial projection-type algorithm for solving variational inequality problems in real Hilbert spaces where the underline operator is…

Optimization and Control · Mathematics 2021-01-25 Yekini Shehu , Olaniyi. S. Iyiola , Xiao-Huan Li , Qiao-Li Dong

We give efficient algorithms for volume sampling, i.e., for picking $k$-subsets of the rows of any given matrix with probabilities proportional to the squared volumes of the simplices defined by them and the origin (or the squared volumes…

Data Structures and Algorithms · Computer Science 2010-04-26 Amit Deshpande , Luis Rademacher

We consider the problem of nonparametric regression under shape constraints. The main examples include isotonic regression (with respect to any partial order), unimodal/convex regression, additive shape-restricted regression, and…

Statistics Theory · Mathematics 2018-07-03 Adityanand Guntuboyina , Bodhisattva Sen

Starting from any unital colored PROP $P$, we define a category $P(P)$ of shapes called $P$-propertopes. Presheaves on $P(P)$ are called $P$-propertopic sets. For $0 \leq n \leq \infty$ we define and study $n$-time categorified $P$-algebras…

Category Theory · Mathematics 2013-02-16 Donald Yau

The equidistant subsequence pattern matching problem is considered. Given a pattern string $P$ and a text string $T$, we say that $P$ is an \emph{equidistant subsequence} of $T$ if $P$ is a subsequence of the text such that consecutive…

Data Structures and Algorithms · Computer Science 2020-02-18 Mitsuru Funakoshi , Yuto Nakashima , Shunsuke Inenaga , Hideo Bannai , Masayuki Takeda , Ayumi Shinohara

This paper concerns a spectral estimation problem in which we want to find a spectral density function that is consistent with estimated second-order statistics. It is an inverse problem admitting multiple solutions, and selection of a…

Optimization and Control · Mathematics 2019-08-08 Bin Zhu

This paper introduces a novel concept of interval probability measures that enables the representation of imprecise probabilities, or uncertainty, in a natural and coherent manner. Within an algebra of sets, we introduce a notion of weak…

Statistics Theory · Mathematics 2024-02-06 Marcello Basili , Luca Pratelli

Subgraph isomorphism counting is known as #P-complete and requires exponential time to find the accurate solution. Utilizing representation learning has been shown as a promising direction to represent substructures and approximate the…

Machine Learning · Computer Science 2024-05-14 Xin Liu , Weiqi Wang , Jiaxin Bai , Yangqiu Song