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We use the lace expansion to study the long-distance decay of the two-point function of weakly self-avoiding walk on the integer lattice $\mathbb{Z}^d$ in dimensions $d>4$, in the vicinity of the critical point, and prove an upper bound…

Probability · Mathematics 2022-09-02 Gordon Slade

We study the asymptotic properties of Lasso+mLS and Lasso+Ridge under the sparse high-dimensional linear regression model: Lasso selecting predictors and then modified Least Squares (mLS) or Ridge estimating their coefficients. First, we…

Statistics Theory · Mathematics 2014-01-14 Hanzhong Liu , Bin Yu

We study internal diffusion limited aggregation (DLA) on the two dimensional comb lattice. The comb lattice is a spanning tree of the euclidean lattice, and internal DLA is a random growth model, where simple random walks, starting one at a…

Probability · Mathematics 2014-01-28 Amine Asselah , Houda Rahmani

We investigate the spatial search problem on the two-dimensional square lattice, using the Dirac evolution operator discretised according to the staggered lattice fermion formalism. $d=2$ is the critical dimension for the spatial search…

Quantum Physics · Physics 2011-02-28 Apoorva Patel , K. S. Raghunathan , Md. Aminoor Rahaman

We study the scaling limits of three different aggregation models on the integer lattice Z^d: internal DLA, in which particles perform random walks until reaching an unoccupied site; the rotor-router model, in which particles perform…

Probability · Mathematics 2007-12-31 Lionel Levine

In recent years, non-parametric methods utilizing random walks on graphs have been used to solve a wide range of machine learning problems, but in their simplest form they do not scale well due to the quadratic complexity. In this paper, a…

Machine Learning · Computer Science 2012-10-19 Saeed Amizadeh , Bo Thiesson , Milos Hauskrecht

Real-world data distributions are often highly skewed. This has spurred a growing body of research on long-tailed recognition, aimed at addressing the imbalance in training classification models. Among the methods studied, multiplicative…

Machine Learning · Computer Science 2025-03-11 Naoya Hasegawa , Issei Sato

We study the random connection model driven by a stationary Poisson process. In the first part of the paper, we derive a lace expansion with remainder term in the continuum and bound the coefficients using a new version of the BK…

Probability · Mathematics 2023-12-20 Markus Heydenreich , Remco van der Hofstad , Günter Last , Kilian Matzke

The node-averaged complexity of a problem captures the number of rounds nodes of a graph have to spend on average to solve the problem in the LOCAL model. A challenging line of research with regards to this new complexity measure is to…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-03 Alkida Balliu , Sebastian Brandt , Fabian Kuhn , Dennis Olivetti , Gustav Schmid

Using off-lattice noise reduction it is possible to estimate the asymptotic properties of diffusion-limited aggregation clusters grown in three dimensions with greater accuracy than would otherwise be possible. The fractal dimension of…

Statistical Mechanics · Physics 2009-11-10 Neill E. Bowler , Robin C. Ball

Including spatial structure and stochastic noise invalidates the classical Lotka-Volterra picture of stable regular population cycles emerging in models for predator-prey interactions. Growth-limiting terms for the prey induce a continuous…

Populations and Evolution · Quantitative Biology 2007-05-23 Mauro Mobilia , Ivan T. Georgiev , Uwe C. Tauber

We study the problem of a random walk on a lattice in which bonds connecting nearest neighbor sites open and close randomly in time, a situation often encountered in fluctuating media. We present a simple renormalization group technique to…

adap-org · Physics 2009-10-22 C. D. Levermore , W. Nadler , D. L. Stein

The model of self-avoiding lattice walks and the asymptotic analysis of power-series have been two of the major research themes of Tony Guttmann. In this paper we bring the two together and perform a new analysis of the generating functions…

Statistical Mechanics · Physics 2016-11-03 Iwan Jensen

We consider the enumeration of walks on the non-negative lattice $\mathbb{N}^d$, with steps defined by a set $\mathcal{S} \subset \{-1, 0, 1\}^d \setminus \{\mathbf{0}\}$. Previous work in this area has established asymptotics for the…

Combinatorics · Mathematics 2019-05-09 Stephen Melczer , Mark C. Wilson

Two-dimensional $CP^{N-1}$ models are investigated by Monte Carlo methods on the lattice, for values of $N$ ranging from 2 to 21. Scaling and rotation invariance are studied by comparing different definitions of correlation length $\xi$.…

High Energy Physics - Lattice · Physics 2009-10-22 Massimo Campostrini , Paolo Rossi , Ettore Vicari

We present a new proof of $|x|^{-(d-2)}$ decay of critical two-point functions for spread-out statistical mechanical models on $\mathbb{Z}^d$ above the upper critical dimension, based on the lace expansion and assuming appropriate…

Probability · Mathematics 2026-03-02 Yucheng Liu , Gordon Slade

We propose a new bottom up method to construct tree amplitudes of non-linear sigma model (NLSM) and special Galileon theory (SG), based on assuming the universality of soft behaviors and the double copy structure. We extend the on-shell…

High Energy Physics - Theory · Physics 2026-05-05 Kang Zhou

We study a stochastic predator-prey model on a square lattice, where each of the six species has two superior and two inferior partners. The invasion probabilities between species depend on the predator-prey pair and are supplemented by…

Populations and Evolution · Quantitative Biology 2007-08-25 Matjaz Perc , Attila Szolnoki

A straightforward algorithm for the symbolic computation of higher-order symmetries of nonlinear evolution equations and lattice equations is presented. The scaling properties of the evolution or lattice equations are used to determine the…

solv-int · Physics 2007-05-23 Unal Goktas , Willy Hereman

Learning sketching matrices for fast and accurate low-rank approximation (LRA) has gained increasing attention. Recently, Bartlett, Indyk, and Wagner (COLT 2022) presented a generalization bound for the learning-based LRA. Specifically, for…

Machine Learning · Computer Science 2022-10-14 Shinsaku Sakaue , Taihei Oki
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