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Related papers: Computing the probability of intersection

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We determine the probability $P$ of two independent events $A$ and $B$, which occur randomly $n_A$ and $n_B$ times during a total time $T$ and last for $t_A$ and $t_B$, to occur simultaneously at some point during $T$. Therefore we first…

General Mathematics · Mathematics 2017-01-03 Fabian Schneider

We study chance constrained optimization problems $\min_x f(x)$ s.t. $P(\left\{ \theta: g(x,\theta)\le 0 \right\})\ge 1-\epsilon$ where $\epsilon\in (0,1)$ is the violation probability, when the distribution $P$ is not known to the decision…

Machine Learning · Computer Science 2024-02-13 A Ch Madhusudanarao , Rahul Singh

For an even set of points in the plane, choose a max-sum matching, that is, a perfect matching maximizing the sum of Euclidean distances of its edges. For each edge of the max-sum matching, consider the ellipse with foci at the edge's…

Computational Geometry · Computer Science 2023-11-23 Polina Barabanshchikova , Alexandr Polyanskii

We derive new upper and lower bounds for probabilities that $r$ or at least $r$ from $n$ events occur. These bounds can turn to equalities. The method is discussed as well. It works for measurable space and measures with sign, too. We also…

Probability · Mathematics 2020-08-12 Andrei N. Frolov

The probability of observing $x_t$ at time $t$, given past observations $x_1...x_{t-1}$ can be computed with Bayes' rule if the true generating distribution $\mu$ of the sequences $x_1x_2x_3...$ is known. If $\mu$ is unknown, but known to…

Machine Learning · Computer Science 2016-11-18 Marcus Hutter

We undertake a critical evaluation of recent observational information on $\Omega_m$ and $\Omega_\Lambda$ in order to identify possible sources of systematic errors and effects of simplified statistical analyses. We combine observations for…

Astrophysics · Physics 2009-11-06 S. M. Harun-or-Rashid , M. Roos

We study local computation algorithms (LCA) for maximum matching. An LCA does not return its output entirely, but reveals parts of it upon query. For matchings, each query is a vertex $v$; the LCA should return whether $v$ is matched -- and…

Data Structures and Algorithms · Computer Science 2023-11-17 Soheil Behnezhad , Mohammad Roghani , Aviad Rubinstein

We investigate the estimation of the perimeter of a set by a graph cut of a random geometric graph. For $\Omega \subset D = (0,1)^d$, with $d \geq 2$, we are given $n$ random i.i.d. points on $D$ whose membership in $\Omega$ is known. We…

Statistics Theory · Mathematics 2016-08-16 Nicolás García Trillos , Dejan Slepčev , James von Brecht

In this work, we study the probability distribution for the force and potential energy of a test particle interacting with $N$ point random sources in the limit $N\rightarrow\infty$. The interaction is given by a central potential…

Mathematical Physics · Physics 2023-08-17 E. L. S. Silva , L. H. Miranda-Filho , A. Figueiredo

We present explicit formulas for total crossing events in the multi-species asymmetric exclusion process ($r$-ASEP) with underlying $U_q(\widehat{\mathfrak{sl}}_{r+1})$ symmetry. In the case of the two-species TASEP these can be derived…

Mathematical Physics · Physics 2023-06-05 Jan de Gier , William Mead , Michael Wheeler

Set intersection is a fundamental operation in information retrieval and database systems. This paper introduces linear space data structures to represent sets such that their intersection can be computed in a worst-case efficient way. In…

Databases · Computer Science 2011-03-15 Bolin Ding , Arnd Christian König

For independent random variables $(X_i)_{1\leq i\leq n}$, we consider the maximal correlation coefficient $R=R(\min_{i:1\leq i\leq m}X_i,\min_{j:\ell+1\leq j\leq n}X_j)$. If $X_1,X_2,\ldots,X_n$ are identically distributed with the same…

Probability · Mathematics 2026-03-27 Yinshan Chang , Qinwei Chen

The hypothesis that high dimensional data tend to lie in the vicinity of a low dimensional manifold is the basis of manifold learning. The goal of this paper is to develop an algorithm (with accompanying complexity guarantees) for fitting a…

Statistics Theory · Mathematics 2013-12-23 Charles Fefferman , Sanjoy Mitter , Hariharan Narayanan

We show that under minimal assumptions on a class of functions $\mathcal{H}$ defined on a probability space $(\mathcal{X},\mu)$, there is a threshold $\Delta_0$ satisfying the following: for every $\Delta\geq\Delta_0$, with probability at…

Probability · Mathematics 2025-08-05 Daniel Bartl , Shahar Mendelson

In this article, we generalize known formulas for crossing probabilities. Prior crossing results date back to J. Cardy's prediction of a formula for the probability that a percolation cluster in two dimensions connects the left and right…

Statistical Mechanics · Physics 2018-05-23 Steven M. Flores , Jacob J. H. Simmons , Peter Kleban , Robert M. Ziff

We propose a self-improving algorithm for computing Voronoi diagrams under a given convex distance function with constant description complexity. The $n$ input points are drawn from a hidden mixture of product distributions; we are only…

Computational Geometry · Computer Science 2021-10-26 Siu-Wing Cheng , Man Ting Wong

A novel algorithm is presented for the estimation of collision probabilities between dynamic objects with uncertain trajectories, where the trajectories are given as a sequence of poses with Gaussian distributions. We propose an adaptive…

Robotics · Computer Science 2025-07-09 Charles Champagne Cossette , Taylor Scott Clawson , Andrew Feit

Let $f$ be analytic on $[0,1]$ with $|f^{(k)}(1/2)|\leq A\alpha^kk!$ for some constant $A$ and $\alpha<2$. We show that the median estimate of $\mu=\int_0^1f(x)\,\mathrm{d}x$ under random linear scrambling with $n=2^m$ points converges at…

Computation · Statistics 2022-07-11 Zexin Pan , Art B. Owen

We derive a framework to compute optimal controls for problems with states in the space of probability measures. Since many optimal control problems constrained by a system of ordinary differential equations (ODE) modelling interacting…

Optimization and Control · Mathematics 2020-09-23 Martin Burger , René Pinnau , Claudia Totzeck , Oliver Tse

We consider a sequence of i.i.d. random variables $\{\xi_k\}$under a sublinear expectation $\mathbb{E}=\sup_{P\in\Theta}E_P$. We first give a new proof to the fact that, under each $P\in\Theta$, any cluster point of the empirical averages…

Probability · Mathematics 2022-07-12 Yongsheng Song