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Set functions with convenient properties (such as submodularity) appear in application areas of current interest, such as algorithmic game theory, and allow for improved optimization algorithms. It is natural to ask (e.g., in the context of…

Data Structures and Algorithms · Computer Science 2018-04-02 Uriel Feige , Michal Feldman , Inbal Talgam-Cohen

In this paper we investigate k-submodular functions. This natural family of discrete functions includes submodular and bisubmodular functions as the special cases k = 1 and k = 2 respectively. In particular we generalize the known…

Discrete Mathematics · Computer Science 2013-09-24 Anna Huber , Vladimir Kolmogorov

A geometric grid class consists of those permutations that can be drawn on a specified set of line segments of slope \pm1 arranged in a rectangular pattern governed by a matrix. Using a mixture of geometric and language theoretic methods,…

Combinatorics · Mathematics 2012-02-06 Michael H. Albert , M. D. Atkinson , Mathilde Bouvel , Nik Ruškuc , Vincent Vatter

We enumerate the independent sets of several classes of regular and almost regular graphs and compute the corresponding generating functions. We also note the relations between these graphs and other combinatorial objects and, in some…

Combinatorics · Mathematics 2007-05-23 Alexander Burstein , Sergey Kitaev , Toufik Mansour

In this paper, subgraphs and complementary graphs are used to analyze the network synchronizability. Some sharp and attainable bounds are provided for the eigenratio of the network structural matrix, which characterizes the network…

Networking and Internet Architecture · Computer Science 2009-11-13 Zhisheng Duan , Chao Liu , Guanrong Chen

We derive an explicit isomorphism between the Hilbert modular group and certain congruence subgroups on the one hand and particular subgroups of the special orthogonal group $SO(2, 2)$ on the other hand. The proof is based on an application…

Number Theory · Mathematics 2022-06-14 Adrian Hauffe-Waschbüsch , Aloys Krieg

Modular meta-learning is a new framework that generalizes to unseen datasets by combining a small set of neural modules in different ways. In this work we propose abstract graph networks: using graphs as abstractions of a system's subparts…

Machine Learning · Computer Science 2018-12-20 Ferran Alet , Maria Bauza , Alberto Rodriguez , Tomas Lozano-Perez , Leslie P. Kaelbling

The convergence of multiple Fourier series of functions of bounded partial $% \Lambda$-variation is investigated. The sufficient and necessary conditions on the sequence $\Lambda=\{\lambda_n\}$ are found for the convergence of multiple…

Analysis of PDEs · Mathematics 2012-10-17 Ushangi Goginava , Artur Sahakian

Modular graph forms are a class of modular covariant functions which appear in the genus-one contribution to the low-energy expansion of closed string scattering amplitudes. Modular graph forms with holomorphic subgraphs enjoy the…

High Energy Physics - Theory · Physics 2019-02-20 Jan E. Gerken , Justin Kaidi

In this paper, we study classes of discrete convex functions: submodular functions on modular semilattices and L-convex functions on oriented modular graphs. They were introduced by the author in complexity classification of minimum…

Optimization and Control · Mathematics 2016-10-11 Hiroshi Hirai

We compare two classes of functions arising from genus-one superstring amplitudes: modular and holomorphic graph functions. We focus on their analytic properties, we recall the known asymptotic behaviour of modular graph functions and we…

Mathematical Physics · Physics 2018-07-13 Federico Zerbini

In this paper, we deal with a notion of Banach space-valued mappings defined on a set consisting of finite graphs with uniformly bounded vertex degree. These functions will be endowed with certain boundedness and additivity criteria. We…

Combinatorics · Mathematics 2015-01-14 Felix Pogorzelski

We present an exploration of the rich theoretical connections between several classes of regularized models, network flows, and recent results in submodular function theory. This work unifies key aspects of these problems under a common…

Machine Learning · Statistics 2013-12-09 Hoyt Koepke , Marina Meila

Mock threshold graphs are a simple generalization of threshold graphs that, like threshold graphs, are perfect graphs. Our main theorem is a characterization of mock threshold graphs by forbidden induced subgraphs. Other theorems…

Combinatorics · Mathematics 2021-06-16 Richard Behr , Vaidy Sivaraman , Thomas Zaslavsky

In this technical report we describe a general class of monoids for which (sub)sequential rational can be characterised in terms of a congruence relation in the flavour of Myhill-Nerode relation. The class of monoids that we consider can be…

Formal Languages and Automata Theory · Computer Science 2018-01-31 Stefan Gerdjikov

In a seminal paper, Choquet introduced an integral formula to extend a monotone increasing setfunction on a sigma-algebra to a (nonlinear) functional on bounded measurable functions. The most important special case is when the setfunction…

Combinatorics · Mathematics 2025-04-29 László Lovász

We prove several combinatorial results on path algebras over discrete structures related to directed graphs. These results are motivated by Morse theory on a manifold with boundary and, more generally, by Floer theory on a configuration…

Geometric Topology · Mathematics 2013-01-01 Jonathan M. Bloom

Networks are frequently studied algebraically through matrices. In this work, we show that networks may be studied in a more abstract level using results from the theory of matroids by establishing connections to networks by decomposition…

Combinatorics · Mathematics 2015-11-17 Konstantinos Papalamprou , Leonidas Pitsoulis

In this manuscript, we offer a gentle review of submodularity and supermodularity and their properties. We offer a plethora of submodular definitions; a full description of a number of example submodular functions and their generalizations;…

Machine Learning · Computer Science 2022-10-05 Jeff Bilmes

A set label disagreement function is defined over the number of variables that deviates from the dominant label. The dominant label is the value assumed by the largest number of variables within a set of binary variables. The submodularity…

Computer Vision and Pattern Recognition · Computer Science 2013-07-05 Toufiq Parag
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