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Bayesian networks, and especially their structures, are powerful tools for representing conditional independencies and dependencies between random variables. In applications where related variables form a priori known groups, chosen to…

Machine Learning · Statistics 2017-06-02 Pekka Parviainen , Samuel Kaski

Link prediction, or the inference of future or missing connections between entities, is a well-studied problem in network analysis. A multitude of heuristics exist for link prediction in ordinary networks with a single type of connection.…

Machine Learning · Computer Science 2020-04-10 Robert E. Tillman , Vamsi K. Potluru , Jiahao Chen , Prashant Reddy , Manuela Veloso

Existing evaluations of entity linking systems often say little about how the system is going to perform for a particular application. There are two fundamental reasons for this. One is that many evaluations only use aggregate measures…

Computation and Language · Computer Science 2023-11-20 Hannah Bast , Matthias Hertel , Natalie Prange

The determination of cluster centers generally depends on the scale that we use to analyze the data to be clustered. Inappropriate scale usually leads to unreasonable cluster centers and thus unreasonable results. In this study, we first…

Machine Learning · Statistics 2016-10-20 Xiurui Geng , Hairong Tang

This paper initiates the dialectical approach to net theory. This approach views nets as special, but very important and natural, dialectical systems. By following this approach, a suitably generalized version of nets, called dialectical…

Logic in Computer Science · Computer Science 2018-10-16 Robert E. Kent

In this thesis, we develop various techniques for working with sets in machine learning. Each input or output is not an image or a sequence, but a set: an unordered collection of multiple objects, each object described by a feature vector.…

Machine Learning · Computer Science 2021-03-09 Yan Zhang

Lie systems form a class of systems of first-order ordinary differential equations whose general solutions can be described in terms of certain finite families of particular solutions and a set of constants, by means of a particular type of…

Mathematical Physics · Physics 2013-03-13 J. F. Cariñena , J. de Lucas

A coreset is a small set that can approximately preserve the structure of the original input data set. Therefore we can run our algorithm on a coreset so as to reduce the total computational complexity. Conventional coreset techniques…

Machine Learning · Computer Science 2022-10-11 Jiaxiang Chen , Qingyuan Yang , Ruomin Huang , Hu Ding

One of the well-known results in concurrency theory concerns the relationship between event structures and occurrence nets: an occurrence net can be associated with a prime event structure, and vice versa. More generally, the relationships…

Logic in Computer Science · Computer Science 2019-10-25 Hernán Melgratti , Claudio Antares Mezzina , Iain Phillips , G. Michele Pinna , Irek Ulidowski

Factor systems are a tool for working on the extension problem of algebraic structures such as groups, Lie algebras, and associative algebras. Their applications are numerous and well-known in these common settings. We construct…

Rings and Algebras · Mathematics 2021-05-04 Erik Mainellis

An active research line within the broader field of network science is the one concerning link prediction. Close in scope to network reconstruction, link prediction targets specific connections with the aim of uncovering the missing ones,…

Physics and Society · Physics 2026-02-02 Francesca Santucci , Giulio Cimini , Tiziano Squartini

A matching from a finite subset $A$ of an abelian group $G$ to another subset $B$ is a bijection $f : A \to B$ such that $af(a) \notin A$ for all $a \in A$. The study of matchings began in the 1990s and was motivated by a conjecture of E.…

Combinatorics · Mathematics 2025-08-05 Mohsen Aliabadi , Jozsef Losonczy

Bipartite networks provide an effective resource for representing, characterizing, and modeling several abstract and real-world systems and structures involving binary relations, which include food webs, social interactions, and…

Social and Information Networks · Computer Science 2024-02-01 Alexandre Benatti , Luciano da F. Costa

Rank-based linkage is a new tool for summarizing a collection $S$ of objects according to their relationships. These objects are not mapped to vectors, and ``similarity'' between objects need be neither numerical nor symmetrical. All an…

Combinatorics · Mathematics 2026-03-25 R. W. R. Darling , Will Grilliette , Adam Logan

Looking to overcome the limitations of traditional networks, the network science community has lately given much attention to the so-called higher-order networks, where group interactions are modeled alongside pairwise ones. While degree…

Physics and Society · Physics 2022-07-11 Demival Vasques Filho

Let $B$ be an arrangement of linear complex hyperplanes in $C^d$. Then a classical result by Orlik \& Solomon asserts that the cohomology algebra of the complement can be constructed from the combinatorial data that are given by the…

alg-geom · Mathematics 2008-02-03 Günter M. Ziegler

Separation systems are posets with additional structure that form an abstract setting in which tangle-like clusters in graphs, matroids and other combinatorial structures can be expressed and studied. This paper offers some basic theory…

Combinatorics · Mathematics 2025-05-16 Reinhard Diestel , Jay Lilian Kneip

This work considers special types of interval linear systems - overdetermined systems. Simply said these systems have more equations than variables. The solution set of an interval linear system is a collection of all solutions of all…

Numerical Analysis · Computer Science 2013-04-18 Jaroslav Horáček , Milan Hladík

Among topics of opinion formation it is of interest to observe the characteristics of networks with a priori distinct communities. As an illustration, we report on the citation network(s) unfolded in the recent decades through web available…

Physics and Society · Physics 2012-09-04 G. Rotundo , M. Ausloos

The goal of confidence-set learning in the binary classification setting is to construct two sets, each with a specific probability guarantee to cover a class. An observation outside the overlap of the two sets is deemed to be from one of…

Machine Learning · Statistics 2018-10-01 Wenbo Wang , Xingye Qiao