English
Related papers

Related papers: Statistical outliers in random laser emission

200 papers

It is known that if one perturbs a large iid random matrix by a bounded rank error, then the majority of the eigenvalues will remain distributed according to the circular law. However, the bounded rank perturbation may also create one or…

Probability · Mathematics 2015-03-17 Terence Tao

The development of effective knowledge discovery techniques has become in the recent few years a very active research area due to the important impact it has in several relevant application areas. One interesting task thereof is that of…

Artificial Intelligence · Computer Science 2007-05-23 Fabrizio Angiulli , Gianluigi Greco , Luigi Palopoli

Normalization and outlier detection belong to the preprocessing of gene expression data. We propose a natural normalization procedure based on statistical data depth which normalizes to the distribution of gene expressions of the most…

Methodology · Statistics 2022-06-29 Alicia Nieto-Reyes , Javier Cabrera

Anomaly detection aims at identifying data points that show systematic deviations from the majority of data in an unlabeled dataset. A common assumption is that clean training data (free of anomalies) is available, which is often violated…

Machine Learning · Computer Science 2022-07-20 Chen Qiu , Aodong Li , Marius Kloft , Maja Rudolph , Stephan Mandt

A new technique for the detection of outliers in contingency tables is introduced. Outliers thereby are unexpected cell counts with respect to classical loglinear Poisson models. Subsets of cell counts called minimal patterns are defined,…

Computation · Statistics 2012-11-15 Sonja Kuhnt , Fabio Rapallo , André Rehage

Outlier detection is an inevitable step to most statistical data analyses. However, the mere detection of an outlying case does not always answer all scientific questions associated with that data point. Outlier detection techniques,…

Methodology · Statistics 2019-12-12 Michiel Debruyne , Sebastiaan Höppner , Sven Serneels , Tim Verdonck

With the upcoming plethora of astronomical time-domain datasets and surveys, anomaly detection as a way to discover new types of variable stars and transients has inspired a new wave of research. Yet, the fundamental definition of what…

Solar and Stellar Astrophysics · Physics 2023-01-26 Dennis A. Crake , Juan Rafael Martínez-Galarza

Rare events in stochastic processes with heavy-tailed distributions are controlled by the big jump principle, which states that a rare large fluctuation is produced by a single event and not by an accumulation of coherent small deviations.…

Statistical Mechanics · Physics 2020-03-13 Raffaella Burioni , Alessandro Vezzani

We investigate multiple scattering of near-resonant light in a Doppler-broadened atomic vapor. We experimentally characterize the length distribution of the steps between successive scattering events. The obtained power law is…

Atomic Physics · Physics 2013-06-26 Nicolas Mercadier , Martine Chevrollier , William Guerin , Robin Kaiser

Extreme Scattering Events are radio-wave lensing events caused by AU-sized concentrations of ionised gas. Although they were discovered more than a decade ago we still have no clear picture of the physical nature of the lenses. To…

Astrophysics · Physics 2007-05-23 Mark A. Walker

Event sequence data record the occurrences of events in continuous time. Event sequence forecasting based on temporal point processes (TPPs) has been extensively studied, but outlier or anomaly detection, especially without any supervision…

Machine Learning · Computer Science 2024-11-26 Somjit Nath , Yik Chau Lui , Siqi Liu

We present an unsupervised search for outliers in the Bright Galaxy Survey (BGS) dataset from the DESI Early Data Release. This analysis utilizes an autoencoder to compress galaxy spectra into a compact, redshift-invariant latent space, and…

Astrophysics of Galaxies · Physics 2023-07-18 Yan Liang , Peter Melchior , ChangHoon Hahn , Jeff Shen , Andy Goulding , Charlotte Ward

Outlier detection is a core task in data mining with a plethora of algorithms that have enjoyed wide scale usage. Existing algorithms are primarily focused on detection, that is the identification of outliers in a given dataset. In this…

Machine Learning · Computer Science 2019-11-11 Yue Wu , Leman Akoglu , Ian Davidson

We present a methodology to discover outliers in catalogs of periodic light-curves. We use cross-correlation as measure of ``similarity'' between two individual light-curves and then classify light-curves with lowest average ``similarity''…

Astrophysics · Physics 2009-11-11 P. Protopapas , J. M. Giammarco , L. Faccioli , M. F. Struble , R. Dave , C. Alcock

Consider the random bipartite Erd\H{o}s-R\'{e}nyi graph $\mathbb{G}(n, m, p)$, where each edge with one vertex in $V_{1}=[n]$ and the other vertex in $V_{2} =[m]$ is connected with probability $p$, and $n=\lfloor \gamma m\rfloor$ for a…

Probability · Mathematics 2025-09-03 Ioana Dumitriu , Hai-Xiao Wang , Zhichao Wang , Yizhe Zhu

Outliers are the points which are different from or inconsistent with the rest of the data. They can be novel, new, abnormal, unusual or noisy information. Outliers are sometimes more interesting than the majority of the data. The main…

Computer Vision and Pattern Recognition · Computer Science 2014-06-20 Singh Vijendra , Pathak Shivani

Reliable outlier detection in high-dimensional data is crucial in modern science, yet it remains a challenging task. Traditional methods often break down in these settings due to their reliance on asymptotic behaviors with respect to sample…

Methodology · Statistics 2025-11-05 Seong-ho Lee , Yongho Jeon

L\'evy flights for light have been demonstrated in disordered systems with and without optical gain, and remained unobserved in ordered ones. In the present letter, we investigate, numerically and experimentally, L\'evy flights for light in…

Outlier detection is a major topic in robust statistics due to the high practical significance of anomalous observations. Many existing methods are, however, either parametric or cease to perform well when the data is far from linearly…

Methodology · Statistics 2018-11-14 Matias Heikkilä

For fixed positive integers m, we consider the product of m independent n by n random matrices with iid entries as in the limit as n tends to infinity. Under suitable assumptions on the entries of each matrix, it is known that the limiting…

Probability · Mathematics 2017-11-21 Natalie Coston , Sean O'Rourke , Philip Matchett Wood