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相关论文: Stochastic decomposition for $\ell_p$-norm symmetr…

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The classic problems of testing uniformity of and learning a discrete distribution, given access to independent samples from it, are examined under general $\ell_p$ metrics. The intuitions and results often contrast with the classic…

数据结构与算法 · 计算机科学 2015-03-24 Bo Waggoner

Stochastic simulation algorithms such as likelihood weighting often give fast, accurate approximations to posterior probabilities in probabilistic networks, and are the methods of choice for very large networks. Unfortunately, the special…

人工智能 · 计算机科学 2016-11-26 Keiji Kanazawa , Daphne Koller , Stuart Russell

Eldan's stochastic localization is a probabilistic construction that has proved instrumental to modern breakthroughs in high-dimensional geometry and the design of sampling algorithms. Motivated by sampling under non-Euclidean geometries…

概率论 · 数学 2026-03-18 Anming Gu , Bobby Shi , Kevin Tian

We analyze a stochastic approximation algorithm for decision-dependent problems, wherein the data distribution used by the algorithm evolves along the iterate sequence. The primary examples of such problems appear in performative prediction…

最优化与控制 · 数学 2024-05-15 Joshua Cutler , Mateo Díaz , Dmitriy Drusvyatskiy

The problem of non-iterative one-shot and non-destructive correction of unavoidable mistakes arises in all Artificial Intelligence applications in the real world. Its solution requires robust separation of samples with errors from samples…

机器学习 · 计算机科学 2017-09-05 A. N. Gorban , I. Y. Tyukin

We study the distribution of a general class of asymptoticallylinear statistics which are symmetric functions of $N$ independent observations. The distribution functions of these statistics are approximated by an Edgeworth expansion with a…

统计理论 · 数学 2021-02-09 Friedrich Götze , Mindaugas Bloznelis

Consider a probability measure supported by a regular geodesic ball in a manifold. For any p larger than or equal to 1 we define a stochastic algorithm which converges almost surely to the p-mean of the measure. Assuming furthermore that…

概率论 · 数学 2011-06-28 Marc Arnaudon , Clément Dombry , Anthony Phan , Le Yang

We investigate the problem of ballistically controlled reactions where particles either annihilate upon collision with probability $p$, or undergo an elastic shock with probability $1-p$. Restricting to homogeneous systems, we provide in…

统计力学 · 物理学 2007-05-23 Francois Coppex , Michel Droz , Emmanuel Trizac

This article investigates, by probabilistic methods, various geometric questions on B_p^n, the unit ball of \ell_p^n. We propose realizations in terms of independent random variables of several distributions on B_p^n, including the…

概率论 · 数学 2007-05-23 Franck Barthe , Olivier Guedon , Shahar Mendelson , Assaf Naor

The standard quadratic optimization problem (StQP) consists of minimizing a quadratic form over the standard simplex. Without convexity or concavity of the quadratic form, the StQP is NP-hard. This problem has many relevant real-life…

最优化与控制 · 数学 2025-04-10 Immanuel M. Bomze , Daniel de Vicente

We present an application of the theory of stochastic processes to model and categorize non-equilibrium physical phenomena. The concepts of uniformly continuous probability measures and modular evolution lead to a systematic hierarchical…

数学物理 · 物理学 2009-08-18 Enrique Hernandez-Lemus , Jesus K. Estrada-Gil

Optimal transport (OT) defines a powerful framework to compare probability distributions in a geometrically faithful way. However, the practical impact of OT is still limited because of its computational burden. We propose a new class of…

最优化与控制 · 数学 2016-05-30 Genevay Aude , Marco Cuturi , Gabriel Peyré , Francis Bach

We present novel bounds for estimating discrete probability distributions under the $\ell_\infty$ norm. These are nearly optimal in various precise senses, including a kind of instance-optimality. Our data-dependent convergence guarantees…

统计理论 · 数学 2024-02-14 Aryeh Kontorovich , Amichai Painsky

The path probability of stochastic motion of non dissipative or quasi-Hamiltonian systems is investigated by numerical experiment. The simulation model generates ideal one-dimensional motion of particles subject only to conservative forces…

统计力学 · 物理学 2015-03-20 Tongling Lin , Ru Wang , W. P. Bi , A. El Kaabouchi , C. Pujos , F. Calvayrac , Q. A. Wang

Given two discrete random variables $X$ and $Y$, with probability distributions ${\bf p} =(p_1, \ldots , p_n)$ and ${\bf q}=(q_1, \ldots , q_m)$, respectively, denote by ${\cal C}({\bf p}, {\bf q})$ the set of all couplings of ${\bf p}$ and…

信息论 · 计算机科学 2017-03-29 Ferdinando Cicalese , Luisa Gargano , Ugo Vaccaro

Nonsmooth nonconvex optimization problems involving the $\ell^p$ quasi-norm, $p \in (0, 1]$, of a linear map are considered. A monotonically convergent scheme for a regularized version of the original problem is developed and necessary…

最优化与控制 · 数学 2017-09-20 Daria Ghilli , Karl Kunisch

We introduce a method to sample the orientational distribution function in computer simulations. The method is based on the exact torque balance equation for classical many-body systems of interacting anisotropic particles in equilibrium.…

软凝聚态物质 · 物理学 2023-04-12 Johannes Renner , Matthias Schmidt , Daniel de las Heras

We derive optimal-order homogenization rates for random nonlinear elliptic PDEs with monotone nonlinearity in the uniformly elliptic case. More precisely, for a random monotone operator on $\mathbb{R}^d$ with stationary law (i.e. spatially…

偏微分方程分析 · 数学 2021-01-01 Julian Fischer , Stefan Neukamm

Let $(X,Y)$ be a random couple in $S\times T$ with unknown distribution $P$ and $(X_1,Y_1),...,(X_n,Y_n)$ be i.i.d. copies of $(X,Y).$ Denote $P_n$ the empirical distribution of $(X_1,Y_1),...,(X_n,Y_n).$ Let $h_1,...,h_N:S\mapsto [-1,1]$…

统计理论 · 数学 2009-05-14 Vladimir Koltchinskii

Stochastic optimization problems often involve data distributions that change in reaction to the decision variables. This is the case for example when members of the population respond to a deployed classifier by manipulating their features…

最优化与控制 · 数学 2020-12-15 Dmitriy Drusvyatskiy , Lin Xiao
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