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Graph inference plays an essential role in machine learning, pattern recognition, and classification. Signal processing based approaches in literature generally assume some variational property of the observed data on the graph. We make a…

Information Theory · Computer Science 2020-08-24 B. Subbareddy , Aditya Siripuram , Jingxin Zhang

We prove that many sequences of positive numbers $(a_n)$ defined by finite linear difference equations $a_{n+k}=c_{k-1}a_{n+k-1}+...+c_0a_n$ with suitable non negative reals coefficients $c_i$ satisfy Bendford's Law on the first digit in…

Dynamical Systems · Mathematics 2010-08-18 Hugues Deligny , Paul Jolissaint

Despite their ability to represent highly expressive functions, deep learning models seem to find simple solutions that generalize surprisingly well. Spectral bias -- the tendency of neural networks to prioritize learning low frequency…

Machine Learning · Computer Science 2022-09-30 Sara Fridovich-Keil , Raphael Gontijo-Lopes , Rebecca Roelofs

The generalized gamma distribution shows up in many problems related to engineering, hydrology as well as survival analysis. Earlier work has been done that estimated the deviation of the exponential and the Weibull distribution from…

Probability · Mathematics 2022-11-10 Zelong Bi , Irfan Durmić , Steven J. Miller

Deep learning has recently revealed the existence of scaling laws, demonstrating that model performance follows predictable trends based on dataset and model sizes. Inspired by these findings and fascinating phenomena emerging in the…

Machine Learning · Statistics 2026-02-10 Mattia Rosso , Simone Rossi , Giulio Franzese , Markus Heinonen , Maurizio Filippone

The supersymmetric standard model with supergravity-inspired soft breaking terms predicts a rich pectrum of sparticles to be discovered at the SSC, LHC and NLC. Because there are more supersymmetric particles than unknown parameters, one…

High Energy Physics - Phenomenology · Physics 2011-03-04 Stephen P. Martin , Pierre Ramond

Monitoring of networks for anomaly detection has attracted a lot of attention in recent years especially with the rise of connected devices and social networks. This is of importance as anomaly detection could span a wide range of…

Applications · Statistics 2019-05-08 Tomilayo Komolafe , A. Valeria Quevedo , Srijan Sengupta , William H. Woodall

Considering the first significant digits (noted d) in data sets of dissipation for turbulent flows, the probability to find a given number (d=1 or 2 or... 9) would be 1/9 for an uniform distribution. Instead the probability closely follows…

Fluid Dynamics · Physics 2015-11-18 Damien Biau

Nonuniform Fourier data are routinely collected in applications such as magnetic resonance imaging, synthetic aperture radar, and synthetic imaging in radio astronomy. To acquire a fast reconstruction that does not require an online inverse…

Numerical Analysis · Mathematics 2016-10-05 Anne Gelb , Guohui Song

It is known that increasing powers of a continuous random variable converge in distribution to Benford's law as the exponent approaches infinity. The rate of convergence has been estimated using Fourier analysis, but we present an…

Probability · Mathematics 2013-07-23 Michał Ryszard Wójcik

A necessary and sufficient condition ("nonresonance") is established for every solution of an autonomous linear difference equation, or more generally for every sequence $(x^\top A^n y)$ with $x,y\in \mathbb{R}^d$ and $A\in…

Dynamical Systems · Mathematics 2014-07-24 Arno Berger , Gideon Eshun

The early research report explores the possibility of using Graph Neural Networks (GNNs) for anomaly detection in internet traffic data enriched with information. While recent studies have made significant progress in using GNNs for anomaly…

Social and Information Networks · Computer Science 2024-05-24 Anasuya Chattopadhyay , Daniel Reti , Hans D. Schotten

NetFlow data is a popular network log format used by many network analysts and researchers. The advantages of using NetFlow over deep packet inspection are that it is easier to collect and process, and it is less privacy intrusive. Many…

Machine Learning · Computer Science 2025-01-09 Clinton Cao , Annibale Panichella , Sicco Verwer , Agathe Blaise , Filippo Rebecchi

Statistical laws describe regular patterns observed in diverse scientific domains, ranging from the magnitude of earthquakes (Gutenberg-Richter law) and metabolic rates in organisms (Kleiber's law), to the frequency distribution of words in…

Physics and Society · Physics 2025-02-14 Eduardo G. Altmann

Gram's Law describes a pattern that frequently occurs in the distribution of the non-trivial zeros of the Riemann zeta function along the critical line. Whenever Gram's Law holds true, it reduces the difficulty of computing the…

Number Theory · Mathematics 2020-06-02 Cătălin Hanga , Christopher Hughes

The online analysis of multi-way data stored in a tensor $\mathcal{X} \in \mathbb{R} ^{I_1 \times \dots \times I_N} $ has become an essential tool for capturing the underlying structures and extracting the sensitive features which can be…

Machine Learning · Computer Science 2020-03-11 Ali Anaissi , Basem Suleiman , Seid Miad Zandavi

Spectra in astroparticle physics are commonly approximated by simple power laws. The steeply falling nature of these power laws, however, makes the detection of additional components rather challenging. This holds true especially, if the…

High Energy Astrophysical Phenomena · Physics 2021-09-22 Tim Ruhe , Wolfgang Rhode

Let $\mathcal{I} \subset \mathbb{N}$ be an infinite subset, and let $\{a_i\}_{i \in \mathcal{I}}$ be a sequence of nonzero real numbers indexed by $\mathcal{I}$ such that there exist positive constants $m, C_1$ for which $|a_i| \leq C_1…

Number Theory · Mathematics 2023-10-03 Evan Chen , Peter S. Park , Ashvin Swaminathan

Many natural and social systems develop complex networks, that are usually modelled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semi-circle law is known to…

Statistical Mechanics · Physics 2009-11-07 Illes J. Farkas , Imre Derenyi , Albert-Laszlo Barabasi , Tamas Vicsek

Conformity with Benford's Law is widely used to detect irregularities in numerical datasets, particularly in accounting, finance, and economics. However, the statistical tools commonly used for this purpose (such as Chi-squared, MAD, or KS)…

Econometrics · Economics 2025-06-17 Manuel Cano-Rodriguez