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We introduce a new computational model for data streams: asymptotically exact streaming algorithms. These algorithms have an approximation ratio that tends to one as the length of the stream goes to infinity while the memory used by the…

Data Structures and Algorithms · Computer Science 2014-08-11 Marc Heinrich , Alexander Munteanu , Christian Sohler

Given a labeled graph, the frequent-subgraph mining (FSM) problem asks to find all the $k$-vertex subgraphs that appear with frequency greater than a given threshold. FSM has numerous applications ranging from biology to network science, as…

Data Structures and Algorithms · Computer Science 2018-09-11 Cigdem Aslay , Muhammad Anis Uddin Nasir , Gianmarco De Francisci Morales , Aristides Gionis

Data stream mining aims at extracting meaningful knowledge from continually evolving data streams, addressing the challenges posed by nonstationary environments, particularly, concept drift which refers to a change in the underlying data…

Machine Learning · Computer Science 2025-01-03 Kleanthis Malialis , Jin Li , Christos G. Panayiotou , Marios M. Polycarpou

Suppose that under the action of gravity, liquid drains through the unit $d$-cube via a minimal-length network of channels constrained to pass through random sites and to flow with nonnegative component in one of the canonical orthogonal…

Probability · Mathematics 2010-09-01 Mathew D. Penrose , Andrew R. Wade

Traditional models of wormlike chains in shear flows at finite temperature approximate the equation of motion via finite difference discretization (bead and rod models). We introduce here a new method based on a spectral representation in…

Soft Condensed Matter · Physics 2007-05-23 Chris H. Wiggins , Alberto Montesi , Matteo Pasquali

Switching dynamical systems provide a powerful, interpretable modeling framework for inference in time-series data in, e.g., the natural sciences or engineering applications. Since many areas, such as biology or discrete-event systems, are…

Machine Learning · Computer Science 2021-09-30 Lukas Köhs , Bastian Alt , Heinz Koeppl

Graph compression is a data analysis technique that consists in the replacement of parts of a graph by more general structural patterns in order to reduce its description length. It notably provides interesting exploration tools for the…

Data Structures and Algorithms · Computer Science 2018-07-19 Robin Lamarche-Perrin

We review a recent approach to the mean-field limits in neural networks that takes into account the stochastic nature of input current and the uncertainty in synaptic coupling. This approach was proved to be a rigorous limit of the network…

Probability · Mathematics 2010-01-22 Jonathan Touboul , Bard Ermentrout , Olivier Faugeras , Bruno Cessac

The planar problem of a viscous laminar flow around elliptical cylinders under angle of attack is considered. From the solution of the laminar boundary layer equations using the Loytsyansky local similarity method, the shear stress at the…

Fluid Dynamics · Physics 2021-06-29 Alexander G. Petrov , Artem D. Sukhov

Cascades on random networks are typically analyzed by assuming they map onto percolation processes and then are solved using generating function formulations. This approach assumes that the network is infinite and weakly connected, yet…

Physics and Society · Physics 2013-05-29 Daniel E. Whitney

We study reaction-diffusion particle systems with several interaction mechanisms. As the number of particles tends to infinity, the system admits a mean-field limit describing the bulk behaviour. We focus on determining the propagation…

Probability · Mathematics 2026-04-21 Matthieu Jonckheere , Seva Shneer

Graph representations offer powerful and intuitive ways to describe data in a multitude of application domains. Here, we consider stochastic processes generating graphs and propose a methodology for detecting changes in stationarity of such…

Machine Learning · Computer Science 2021-02-11 Daniele Zambon , Cesare Alippi , Lorenzo Livi

Streamer ionization fronts are pulled fronts propagating into a linearly unstable state; the spatial decay of the initial condition of a planar front selects dynamically one specific long time attractor out of a continuous family. A…

Pattern Formation and Solitons · Physics 2009-11-13 Gianne Derks , Ute Ebert , Bernard Meulenbroek

An anomalous diffusion model for ion channel gating is put forward. This scheme is able to describe non-exponential, power-law like distributions of residence time intervals in several types of ion channels. Our method presents a…

Biological Physics · Physics 2007-05-23 Igor Goychuk , Peter Hanggi

We present an analysis of the mechanics of thin streams, which are formed following the tidal disruption of cold, low-mass clusters in the potential of a massive host galaxy. The analysis makes extensive use of action-angle variables, in…

Astrophysics of Galaxies · Physics 2011-04-14 Andy Eyre , James Binney

We construct a class of discontinuous superprocesses with dependent spatial motion and general branching mechanism. The process arises as the weak limit of critical interacting-branching particle systems where the spatial motions of the…

Probability · Mathematics 2008-07-02 Hui He

We consider dynamics of the empirical measure of vertex neighborhood states of Markov interacting jump processes on sparse random graphs, in a suitable asymptotic limit as the graph size goes to infinity. Under the assumption of a certain…

Probability · Mathematics 2025-02-10 Juniper Cocomello , Michel Davydov , Kavita Ramanan

We propose a novel multiple-scale spatial marching method for flows with slow streamwise variation. The key idea is to couple the boundary region equations, which govern large-scale flow evolution, with local exact coherent structures that…

Fluid Dynamics · Physics 2026-01-14 Runjie Song , Kengo Deguchi

The spatial non-uniformity of the electric field in air discharges, such as streamers, can influence the accuracy of spectroscopic diagnostic methods and hence the estimation of the peak electric field. In this work, we use a…

Atmospheric and Oceanic Physics · Physics 2019-10-15 A. Malagón-Romero , F. J. Pérez-Invernón , A. Luque , F. J. Gordillo-Vázquez

We reconsider the problem of diffusion of particles at constant speed and present a generalization of the Telegrapher process to higher dimensional stochastic media ($d>1$), where the particle can move along $2^d$ directions. We derive the…

Disordered Systems and Neural Networks · Physics 2009-10-31 S. Anantha Ramakrishna , N. Kumar