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We study the expected $\mathcal{L}_2$-discrepancy of stratified samples generated from special equi-volume partitions of the unit square. The partitions are defined via parallel lines that are all orthogonal to the diagonal of the square.…

Number Theory · Mathematics 2024-01-02 Florian Pausinger

We study the expected $ L_2-$discrepancy under two classes of partitions, explicit and exact formulas are derived respectively. These results attain better expected $L_2-$discrepancy formulas than jittered sampling.

Computation · Statistics 2023-03-13 Jun Xian , Xiaoda Xu

We investigate the expected star discrepancy under a newly designed class of convex equivolume partition models. The main contributions are two-fold. First, we establish a strong partition principle for the star discrepancy, showing that…

Probability · Mathematics 2026-01-09 Xiaoda Xu , Jun Xian

For $m, d \in \mathbb{N}$, a jittered sample of $N=m^d$ points can be constructed by partitioning $[0,1]^d$ into $m^d$ axis-aligned equivolume boxes and placing one point independently and uniformly at random inside each box. We utilise a…

Probability · Mathematics 2022-09-13 Nathan Kirk , Florian Pausinger

This paper studies the expected $L_p$-discrepancy ($2 \leq p < \infty$) for stratified sampling schemes under importance sampling. We introduce a parametric family of equivolume partitions $\Omega_{\theta,\sim}$ and leverage recent exact…

Numerical Analysis · Mathematics 2026-01-09 Xiaoda Xu

We study the expected star discrepancy under a newly designed class of non-equal volume partitions. The main contributions are twofold. First, we establish a strong partition principle for the star discrepancy, showing that our newly…

Machine Learning · Statistics 2026-03-10 Xiaoda Xu

We extend the notion of jittered sampling to arbitrary partitions and study the discrepancy of the related point sets. Let $\mathbf{\Omega}=(\Omega_1,\ldots,\Omega_N)$ be a partition of $[0,1]^d$ and let the $i$th point in $\mathcal{P}$ be…

Statistics Theory · Mathematics 2021-02-01 Markus Kiderlen , Florian Pausinger

We prove that classical jittered sampling of the $d$-dimensional unit cube does not yield the smallest expected $\mathcal{L}_2$-discrepancy among all stratified samples with $N=m^d$ points. Our counterexample can be given explicitly and…

Number Theory · Mathematics 2021-10-20 Markus Kiderlen , Florian Pausinger

Classical jittered sampling partitions $[0,1]^d$ into $m^d$ cubes for a positive integer $m$ and randomly places a point inside each of them, providing a point set of size $N=m^d$ with small discrepancy. The aim of this note is to provide a…

Combinatorics · Mathematics 2023-06-30 Francois Clement , Nathan Kirk , Florian Pausinger

We consider random discrepancy under weighted importance sampling of a class of stratified input. We give the expected $L_p-$discrepancy($2\leq p<\infty$) upper bound in weighted form under a class of stratified sampling. This result…

Probability · Mathematics 2025-11-27 Jun Xian , Xiaoda Xu

Bounds on the log partition function are important in a variety of contexts, including approximate inference, model fitting, decision theory, and large deviations analysis. We introduce a new class of upper bounds on the log partition…

Machine Learning · Computer Science 2013-01-07 Martin Wainwright , Tommi S. Jaakkola , Alan Willsky

We study the expected volume of random polytopes generated by taking the convex hull of independent identically distributed points from a given distribution. We show that for log-concave distributions supported on convex bodies, we need at…

Metric Geometry · Mathematics 2021-11-16 Debsoumya Chakraborti , Tomasz Tkocz , Beatrice-Helen Vritsiou

Jittered Sampling is a refinement of the classical Monte Carlo sampling method. Instead of picking $n$ points randomly from $[0,1]^2$, one partitions the unit square into $n$ regions of equal measure and then chooses a point randomly from…

Numerical Analysis · Mathematics 2017-04-20 Florian Pausinger , Manas Rachh , Stefan Steinerberger

In this paper, we study bounds of expected $L_2-$discrepancy to give mean square error of uniform integration approximation for functions in Sobolev space $\mathcal{H}^{\mathbf{1}}(K)$, where $\mathcal{H}$ is a reproducing Hilbert space…

Numerical Analysis · Mathematics 2021-10-05 Jun Xian , Xiaoda Xu

We consider the convex hull of a finite sample of i.i.d. points uniformly distributed in a convex body in $\R^d$, $d\geq 2$. We prove an exponential deviation inequality, which leads to rate optimal upper bounds on all the moments of the…

Statistics Theory · Mathematics 2013-11-13 Victor-Emmanuel Brunel

In this paper we propose an acceptance-rejection sampler using stratified inputs as diver sequence. We estimate the discrepancy of the points generated by this algorithm. First we show an upper bound on the star discrepancy of order…

Computation · Statistics 2014-08-11 Houying Zhu , Josef Dick

For two convex discs $K$ and $L$, we say that $K$ is $L$-convex if it is equal to the intersection of all translates of $L$ that contain $K$. In $L$-convexity the set $L$ plays a similar role as closed half-spaces do in the classical notion…

Metric Geometry · Mathematics 2026-04-09 Ferenc Fodor , Dániel I. Papvári , Viktor Vígh

We present difference schemes for stochastic transport equations with low-regularity velocity fields. We establish $L^2$ stability and convergence of the difference approximations under conditions that are less strict than those required…

Numerical Analysis · Mathematics 2025-01-27 Ulrik S. Fjordholm , Kenneth H. Karlsen , Peter H. C. Pang

The L_2-discrepancy measures the irregularity of the distribution of a finite point set. In this note we prove lower bounds for the L_2 discrepancy of arbitrary N-point sets. Our main focus is on the two-dimensional case. Asymptotic upper…

Numerical Analysis · Mathematics 2014-02-19 Aicke Hinrichs , Lev Markhasin

In this paper, we consider the upper bound of the probabilistic star discrepancy based on Hilbert space filling curve sampling. This problem originates from the multivariate integral approximation, but the main result removes the strict…

Statistics Theory · Mathematics 2023-04-20 Jun Xian , Xiaoda Xu
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