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Related papers: On the Discrepancy of Jittered Sampling

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We consider quantizing an $Ld$-dimensional sample, which is obtained by concatenating $L$ vectors from datasets of $d$-dimensional vectors, to a $d$-dimensional cluster center. The distortion measure is the weighted sum of $r$th powers of…

Machine Learning · Computer Science 2020-10-26 Erdem Koyuncu

Several researchers have proposed minimisation of maximum mean discrepancy (MMD) as a method to quantise probability measures, i.e., to approximate a target distribution by a representative point set. We consider sequential algorithms that…

Machine Learning · Statistics 2021-02-15 Onur Teymur , Jackson Gorham , Marina Riabiz , Chris. J. Oates

Points in the unit cube with low discrepancy can be constructed using algebra or, more recently, by direct computational optimization of a criterion. The usual $L_\infty$ star discrepancy is a poor criterion for this because it is…

Numerical Analysis · Mathematics 2025-08-08 François Clément , Nathan Kirk , Art B. Owen , T. Konstantin Rusch

Given $n$ independent samples from a $d$-dimensional probability distribution, our aim is to generate diffusion-based samples from a distribution obtained by tilting the original, where the degree of tilt is parametrized by $\theta \in…

We study the problem of sampling from a distribution $\mu$ with density $\propto e^{-V}$ for some potential function $V:\mathbb R^d\to \mathbb R$ with query access to $V$ and $\nabla V$. We start with the following standard assumptions: (1)…

Data Structures and Algorithms · Computer Science 2026-02-10 Yuchen He , Zhehan Lei , Jianan Shao , Chihao Zhang

Let $C$ be a convex $d$-dimensional body. If $\rho$ is a large positive number, then the dilated body $\rho C$ contains $\rho^{d}\left\vert C\right\vert +\mathcal{O}\left( \rho^{d-1}\right) $ integer points, where $\left\vert C\right\vert $…

Number Theory · Mathematics 2015-04-14 Giancarlo Travaglini , Maria Rosaria Tupputi

Diffusion models accomplish remarkable success in data generation tasks across various domains. However, the iterative sampling process is computationally expensive. Consistency models are proposed to learn consistency functions to map from…

Machine Learning · Computer Science 2025-05-07 Yiding Chen , Yiyi Zhang , Owen Oertell , Wen Sun

In this paper, we investigate the problem of separating a set $X$ of points in $\mathbb{R}^{2}$ with an arrangement of $K$ lines such that each cell contains an asymptotically equal number of points (up to a constant ratio). We consider a…

Combinatorics · Mathematics 2017-01-18 Nikhil Marda

Consider linear regression where the examples are generated by an unknown distribution on $R^d\times R$. Without any assumptions on the noise, the linear least squares solution for any i.i.d. sample will typically be biased w.r.t. the least…

Machine Learning · Computer Science 2018-10-08 Michał Dereziński , Manfred K. Warmuth , Daniel Hsu

We study density thresholds that force a measurable set $E\subseteq\mathbb{R}^d$ to contain all sufficiently large similar copies of every $n$-point configuration. We prove a lower bound of the form $1-O((\log n)/n)$, which matches the…

Classical Analysis and ODEs · Mathematics 2026-04-21 Vjekoslav Kovač , Adian Anibal Santos Sepčić

We use an entropy based method to study two graph maximization problems. We upper bound the number of matchings of fixed size $\ell$ in a $d$-regular graph on $N$ vertices. For $\frac{2\ell}{N}$ bounded away from 0 and 1, the logarithm of…

Combinatorics · Mathematics 2012-06-15 Teena Carroll , David Galvin , Prasad Tetali

Discretization of the uniform norm of functions from a given finite dimensional subspace of continuous functions is studied. We pay special attention to the case of trigonometric polynomials with frequencies from an arbitrary finite set…

Numerical Analysis · Mathematics 2021-12-14 Boris Kashin , Sergei Konyagin , Vladimir Temlyakov

This paper establishes consistency of the weighted bootstrap for quadratic forms $\left( n^{-1/2} \sum_{i=1}^{n} Z_{i,n} \right)^{T}\left( n^{-1/2} \sum_{i=1}^{n} Z_{i,n} \right)$ where $(Z_{i,n})_{i=1}^{n}$ are mean zero, independent…

Statistics Theory · Mathematics 2018-01-04 Demian Pouzo

A celebrated result of Beck shows that for any set of $N$ points on $\mathbb{S}^d$ there always exists a spherical cap $B \subset \mathbb{S}^d$ such that number of points in the cap deviates from the expected value $\sigma(B) \cdot N$ by at…

Classical Analysis and ODEs · Mathematics 2023-09-13 Dmitriy Bilyk , Michelle Mastrianni , Stefan Steinerberger

Central limit theorems are established for the sum, over a spatial region, of observations from a linear process on a $d$-dimensional lattice. This region need not be rectangular, but can be irregularly-shaped. Separate results are…

Statistics Theory · Mathematics 2016-01-07 S. N. Lahiri , Peter M. Robinson

For distributions $\mathbb{P}$ and $\mathbb{Q}$ with different supports or undefined densities, the divergence $\textrm{D}(\mathbb{P}||\mathbb{Q})$ may not exist. We define a Spread Divergence $\tilde{\textrm{D}}(\mathbb{P}||\mathbb{Q})$ on…

Machine Learning · Statistics 2022-12-06 Mingtian Zhang , Peter Hayes , Tom Bird , Raza Habib , David Barber

Let $(\{1,2,\ldots,n\},d)$ be a metric space. We analyze the expected value and the variance of $\sum_{i=1}^{\lfloor n/2\rfloor}\,d({\boldsymbol{\pi}}(2i-1),{\boldsymbol{\pi}}(2i))$ for a uniformly random permutation ${\boldsymbol{\pi}}$ of…

Data Structures and Algorithms · Computer Science 2017-03-27 Ching-Lueh Chang

We study the notion of $\gamma$-negative dependence of random variables. This notion is a relaxation of the notion of negative orthant dependence (which corresponds to $1$-negative dependence), but nevertheless it still ensures…

Probability · Mathematics 2021-09-21 Benjamin Doerr , Michael Gnewuch

Let $\Sigma_d^{++}$ be the set of positive definite matrices with determinant 1 in dimension $d\ge 2$. Identifying any two $SL_d(\mathbb{Z})$-congruent elements in $\Sigma_d^{++}$ gives rise to the space of reduced quadratic forms of…

Number Theory · Mathematics 2016-07-18 Faustin Adiceam , Evgeniy Zorin

Given a training sample of size $m$ from a $d$-dimensional population, we wish to allocate a new observation $Z\in \R^d$ to this population or to the noise. We suppose that the difference between the distribution of the population and that…

Statistics Theory · Mathematics 2009-03-30 Yuri I. Ingster , Christophe Pouet , Alexandre B. Tsybakov
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