Related papers: When Outliers Are Different

This study concerns the issue of high dimensional outliers which are challenging to distinguish from inliers due to the special structure of high dimensional space. We introduce a new notion of high dimensional outliers that embraces…

We investigate the performance of robust estimates of multivariate location under nonstandard data contamination models such as componentwise outliers (i.e., contamination in each variable is independent from the other variables). This…

We consider a square random matrix of size N of the form A + Y where A is deterministic and Y has iid entries with variance 1/N. Under mild assumptions, as N grows, the empirical distribution of the eigenvalues of A+Y converges weakly to a…

Fast Radio Bursts (FRBs) are a class of short-duration transients at radio wavelengths with inferred astrophysical origin. The prototypical FRB is a broadband signal that occurs over the extent of the receiver frequency range, is narrow in…

It is well-known that real data often contain outliers. The term outlier typically refers to a case, that is, a row of the $n \times d$ data matrix. In recent times a different type has come into focus, the cellwise outliers. These are…

Fast radio bursts (FRBs) are astronomical transients with millisecond timescales occurring at cosmological distances. The observed time lag between different energies of each FRB is well described by the inverse-square law of the observed…

All gravitational-wave signals are inevitably gravitationally lensed by intervening matter as they propagate through the Universe. When a gravitational-wave signal is magnified, it \emph{appears} to have originated from a closer, more…

Since its initial discovery, the Fast radio burst (FRB) FRB 121102 has been found to be repeating with millisecond-duration pulses. Very recently, 15 new bursts were detected by the Green Bank Telescope (GBT) during its continous monitoring…

Central moments and cumulants are often employed to characterize the distribution of data. The skewness and kurtosis are particularly useful for the detection of outliers, the assessment of departures from normally distributed data,…

This paper studies the problem of robustly learning the correlation function for a univariate time series with the presence of noise, outliers and missing entries. The outliers or anomalies considered here are sparse and rare events that…

This paper argues that repeating and apparently non-repeating Fast Radio Bursts are distinct classes of events produced by distinct classes of sources. I review the evidence for that division, and then discusses the statistics of these…

Wireless sensor networks usually comprise a large number of sensors monitoring changes in variables. These changes in variables represent changes in physical quantities. The changes can occur for various reasons; these reasons are…

The discovery of a number of gamma-ray bursts with duration exceeding 1,000 seconds, in particular the exceptional case of GRB 111209A with a duration of about 25,000 seconds, has opened the question on whether these bursts form a new class…

Outlier detection refers to the identification of anomalous samples that deviate significantly from the distribution of normal data and has been extensively studied and used in a variety of practical tasks. However, most unsupervised…

It is now recognized that long-duration Gamma-Ray Bursts (GRBs) are linked to the collapse of massive stars, based on the association between (low-redshift) GRBs and (type Ic) core-collapse supernovae (SNe). The census of massive stars and…

Outlier detection has gained increasing interest in recent years, due to newly emerging technologies and the huge amount of high-dimensional data that are now available. Outlier detection can help practitioners to identify unwanted noise…

There are several methods for obtaining very robust estimates of regression parameters that asymptotically resist 50% of outliers in the data. Differences in the behaviour of these algorithms depend on the distance between the regression…

Fast radio bursts (FRBs) are millisecond-duration extragalactic radio transients. They apparently fall into repeaters and non-repeaters. However, such a classification has lacked a motivation on the physical picture. Here we propose a…

Using methods of statistical mechanics, we analyse the effect of outliers on the supervised learning of a classification problem. The learning strategy aims at selecting informative examples and discarding outliers. We compare two…

Gamma ray bursts (GRBs) are known to have short-time variability and power-law behavior with the index -1.67 in the power spectrum density. Reanalyzing the expanded data, we have found a) the power-law comes from the global profile of the…