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The traditional complex network approach considers only the shortest paths from one node to another, not taking into account several other possible paths. This limitation is significant, for example, in urban mobility studies. In this short…

Discrete Mathematics · Computer Science 2022-10-10 Leonardo B. L. Santos , Luiz Max Carvalho , Giovanni G. Soares , Leonardo N. Ferreira , Igor M. Sokolov

The diameter of the graph of a $d$-dimensional lattice polytope $P \subseteq [0,k]^{n}$ is known to be at most $dk$ due to work by Kleinschmidt and Onn. However, it is an open question whether the monotone diameter, the shortest guaranteed…

Optimization and Control · Mathematics 2022-04-21 Alexander E. Black

An important knowledge dimension of science and technology is the extent to which their development is cumulative, that is, the extent to which later findings build on earlier ones. Cumulative knowledge structures can be studied using a…

Physics and Society · Physics 2021-06-22 P. G. J. Persoon

A method to calculate the average size of Davis-Putnam-Loveland-Logemann (DPLL) search trees for random computational problems is introduced, and applied to the satisfiability of random CNF formulas (SAT) and the coloring of random graph…

Computational Complexity · Computer Science 2008-06-20 Remi Monasson

This paper establishes the (nearly) optimal approximation error characterization of deep rectified linear unit (ReLU) networks for smooth functions in terms of both width and depth simultaneously. To that end, we first prove that…

Machine Learning · Computer Science 2021-11-03 Jianfeng Lu , Zuowei Shen , Haizhao Yang , Shijun Zhang

We introduce an equivalence relation on the set of Dyck paths and some operations on them. We determine a formula for the cardinality of those equivalence classes and use this information to obtain a combinatorial formula for the number of…

Combinatorics · Mathematics 2015-05-11 Stefano Capparelli , Alberto Del Fra

We use purely combinatorial arguments to give a formula to compute all graded Betti numbers of path ideals of line graphs and cycles. As a consequence we can give new and short proofs for the known formulas of regularity and projective…

Commutative Algebra · Mathematics 2017-03-09 Ali Alilooee , Sara Faridi

In the subcritical regime Erd\H{o}s-R\'enyi (ER) networks consist of finite tree components, which are non-extensive in the network size. The distribution of shortest path lengths (DSPL) of subcritical ER networks was recently calculated…

Statistical Mechanics · Physics 2023-11-01 Barak Budnick , Ofer Biham , Eytan Katzav

This paper studies approximation by shallow ReLU$^s$ networks, $\sigma_s(t)=\max\{0,t\}^s$, together with their generalization behavior under $\ell_1$ path-norm control. For the $L^p$-type integral spaces…

Machine Learning · Statistics 2026-05-27 Weizhao Li , Fanghui Liu , Lei Shi

For finite graphs, path-width is an interesting and useful concept, but if we extend it to infinite graphs in the most obvious way (by making the indexing path infinite), it does not work nicely. The simplest extension that works nicely is…

Combinatorics · Mathematics 2025-09-23 Tung Nguyen , Alex Scott , Paul Seymour

We introduce and study the complexity of Path Packing. Given a graph $G$ and a list of paths, the task is to embed the paths edge-disjoint in $G$. This generalizes the well known Hamiltonian-Path problem. Since Hamiltonian Path is…

Computational Complexity · Computer Science 2019-10-02 Jan Dreier , Janosch Fuchs , Tim A. Hartmann , Philipp Kuinke , Peter Rossmanith , Bjoern Tauer , Hung-Lung Wang

We study scalar-linear and vector-linear solutions of the generalized combination network. We derive new upper and lower bounds on the maximum number of nodes in the middle layer, depending on the network parameters and the alphabet size.…

Information Theory · Computer Science 2021-03-12 Hedongliang Liu , Hengjia Wei , Sven Puchinger , Antonia Wachter-Zeh , Moshe Schwartz

We investigate a set of directed sandpile models on the Apollonian network, which are inspired on the work by Dhar and Ramaswamy (PRL \textbf{63}, 1659 (1989)) for Euclidian lattices. They are characterized by a single parameter $q$, that…

Statistical Mechanics · Physics 2011-11-09 André P. Vieira , José S. Andrade , Hans J. Herrmann , Roberto F. S. Andrade

For a complete graph of size $n$, assign each edge an i.i.d. exponential variable with mean $n$. For $\lambda>0$, consider the length of the longest path whose average weight is at most $\lambda$. It was shown by Aldous (1998) that the…

Probability · Mathematics 2013-02-18 Jian Ding

We consider an infinite graph with the vertex set $\mathbb{Z}^2$ and edges connecting the vertices iff the Euclidean distance between the respective points is an integer, and the points do not lie on the same horizontal or vertical.…

Combinatorics · Mathematics 2026-05-21 Jan Willemson

We establish an exact formula for the average number of edges appearing on the boundary of the global convex hull of n independent Brownian paths in the plane. This requires the introduction of a counting criterion which amounts to "cutting…

Statistical Mechanics · Physics 2012-12-10 Julien Randon-Furling

A distributed network is modeled by a graph having $n$ nodes (processors) and diameter $D$. We study the time complexity of approximating {\em weighted} (undirected) shortest paths on distributed networks with a $O(\log n)$ {\em bandwidth…

Data Structures and Algorithms · Computer Science 2014-05-23 Danupon Nanongkai

Computing a shortest path between two nodes in an undirected unweighted graph is among the most basic algorithmic tasks. Breadth first search solves this problem in linear time, which is clearly also a lower bound in the worst case.…

Data Structures and Algorithms · Computer Science 2023-08-01 Noga Alon , Allan Grønlund , Søren Fuglede Jørgensen , Kasper Green Larsen

We study the distribution of a fully connected neural network with random Gaussian weights and biases in which the hidden layer widths are proportional to a large constant $n$. Under mild assumptions on the non-linearity, we obtain…

Machine Learning · Computer Science 2024-06-18 Stefano Favaro , Boris Hanin , Domenico Marinucci , Ivan Nourdin , Giovanni Peccati

Assessing the complexity of functions computed by a neural network helps us understand how the network will learn and generalize. One natural measure of complexity is how the network distorts length - if the network takes a unit-length…

Machine Learning · Statistics 2021-06-24 Boris Hanin , Ryan Jeong , David Rolnick
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