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This paper introduces several depths for random sets with possibly non-convex realisations, proposes ways to estimate the depths based on the samples and compares them with existing ones. The depths are further applied for the comparison…

Methodology · Statistics 2024-02-06 Vesna Gotovac Đogaš

We consider the problem of estimating a spatially varying density function, motivated by problems that arise in large-scale radiological survey and anomaly detection. In this context, the density functions to be estimated are the background…

Methodology · Statistics 2017-11-17 Wesley Tansey , Alex Athey , Alex Reinhart , James G. Scott

We address two shortcomings in online travel time estimation methods for congested urban traffic. The first shortcoming is related to the determination of the number of mixture modes, which can change dynamically, within day and from day to…

Machine Learning · Statistics 2020-01-14 Saif Eddin Jabari , Nikolaos M. Freris , Deepthi Mary Dilip

Flow Matching (FM) has emerged as a powerful paradigm for continuous normalizing flows, yet standard FM implicitly performs an unweighted $L^2$ regression over the entire ambient space. In high dimensions, this leads to a fundamental…

Machine Learning · Statistics 2026-05-26 Shinto Eguchi

We tackle the problem of estimating the spatial distribution of mobile phones from Mobile Network Operator (MNO) data, namely Call Detail Record (CDR) or signalling data. The process of transforming MNO data to a density map requires…

Signal Processing · Electrical Eng. & Systems 2021-11-24 Fabio Ricciato , Angelo Coluccia

This work delves into presenting a probabilistic method for analyzing linear process data with weakly dependent innovations, focusing on detecting change-points in the mean and estimating its spectral density. We develop a test for…

Statistics Theory · Mathematics 2024-10-01 Ramkrishna Jyoti Samanta

We establish statistical properties of random-weighting methods in LASSO regression under different regularization parameters $\lambda_n$ and suitable regularity conditions. The random-weighting methods in view concern repeated optimization…

Methodology · Statistics 2022-05-25 Tun Lee Ng , Michael A. Newton

For a large Hermitian matrix $A\in \mathbb{C}^{N\times N}$, it is often the case that the only affordable operation is matrix-vector multiplication. In such case, randomized method is a powerful way to estimate the spectral density (or…

Numerical Analysis · Mathematics 2015-11-24 Lin Lin

A new method for measuring \ngr cross sections aiming at enhanced signal-to-background ratio is presented. This new approach is based on the combination of the pulse-height weighting technique with a total energy detection system that…

Instrumentation and Detectors · Physics 2015-10-15 César Domingo-Pardo

There has been a growing request from the X-ray astronomy community for a quantitative estimate of systematic uncertainties originating from the atomic data used in plasma codes. Though there have been several studies looking into atomic…

Structural variants compose the majority of human genetic variation, but are difficult to assess using current genomic sequencing technologies. Optical mapping technologies, which measure the size of chromosomal fragments between labeled…

Quantitative Methods · Quantitative Biology 2019-10-10 Weiwei Li , Jan Hannig , Corbin Jones

Unifying the generalized Marshall-Olkin (GMO) and Poisson-G (P-G) a new family of distribution is proposed. Density and the survival function are expressed as infinite mixtures of P-G family. The quantile function, asymptotes, shapes,…

Statistics Theory · Mathematics 2020-06-11 Laba Handique , Farrukh Jamal , Subrata Chakraborty

Many spatial models exhibit locality structures that effectively reduce their intrinsic dimensionality, enabling efficient approximation and sampling of high-dimensional distributions. However, existing approximation techniques primarily…

Machine Learning · Statistics 2026-02-02 Tiangang Cui , Shuigen Liu , Xin T. Tong

Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-based samplers have been proposed in the literature and…

Machine Learning · Statistics 2025-08-12 Xuefeng Gao , Lingjiong Zhu

The performance of all-optical dual-hop relayed free-space optical communication systems is analytically studied and evaluated. We consider the case when the total received signal undergoes turbulence-induced channel fading, modeled by the…

Information Theory · Computer Science 2018-10-18 Nikolaos I. Miridakis , Dimitrios D. Vergados , Angelos Michalas

Two-sample testing is a fundamental problem in statistics. Despite its long history, there has been renewed interest in this problem with the advent of high-dimensional and complex data. Specifically, in the machine learning literature,…

Methodology · Statistics 2019-11-19 Ilmun Kim , Ann B. Lee , Jing Lei

We propose a homotopy sampling procedure, loosely based on importance sampling. Starting from a known probability distribution, the homotopy procedure generates the unknown normalization of a target distribution. In the context of…

Computation · Statistics 2021-05-05 Juan M. Restrepo , Jorge M. Ramirez

Digital constellations formed by hexagonal or other non-square two-dimensional lattices are often used in advanced digital communication systems. The integrals required to evaluate the symbol error rate (SER) of these constellations in the…

Information Theory · Computer Science 2019-02-20 Víctor Elvira , Ignacio Santamaría

In this paper, we study a layered random access scheme based on non-orthogonal multiple access (NOMA) to improve the throughput of multichannel ALOHA. At a receiver, successive interference cancellation (SIC) is carried out across layers to…

Information Theory · Computer Science 2017-12-11 Jinho Choi

The Origin-Destination~(OD) networks provide an estimation of the flow of people from every region to others in the city, which is an important research topic in transportation, urban simulation, etc. Given structural regional urban…

Machine Learning · Computer Science 2023-06-12 Can Rong , Jingtao Ding , Zhicheng Liu , Yong Li
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