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We define a dynamic model of random networks, where new vertices are connected to old ones with a probability proportional to a sublinear function of their degree. We first give a strong limit law for the empirical degree distribution, and…

Probability · Mathematics 2008-07-31 Steffen Dereich , Peter Morters

Percolation has long served as a model for diverse phenomena and systems. The percolation transition, that is, the formation of a giant cluster on a macroscopic scale, is known as one of the most robust continuous transitions. Recently,…

Statistical Mechanics · Physics 2016-12-08 Deokjae Lee , Young Sul Cho , Byungnam Kahng

The relation between thermodynamic phase transitions in classical systems and topology changes in their state space is discussed for systems in which equivalence of statistical ensembles does not hold. As an example, the spherical model…

Statistical Mechanics · Physics 2007-05-23 Michael Kastner

We discuss that how the majority of traditional modeling approaches are following the idealism point of view in scientific modeling, which follow the set theoretical notions of models based on abstract universals. We show that while…

Artificial Intelligence · Computer Science 2017-09-12 Vahid Moosavi

Lexical sets contain the words filling an argument slot of a verb, and are in part determined by selectional preferences. The purpose of this paper is to unravel the properties of lexical sets through distributional semantics. We…

Computation and Language · Computer Science 2020-10-28 Edoardo Maria Ponti , Elisabetta Jezek , Bernardo Magnini

Individual choices often depend on the order in which the decisions are made. In this paper, we expose a general theory of measurable systems (an example of which is an individual's preferences) allowing for incompatible (non-commuting)…

Physics and Society · Physics 2007-06-20 V. I. Danilov , A. Lambert-Mogiliansky

In this short communication, we shall explore a nonlinear discrete dynamical system that naturally occurs in population systems to describe a transmission of a trait from parents to their offspring. We consider a Mendelian inheritance for a…

Dynamical Systems · Mathematics 2013-04-23 Nasir Ganikhodjaev , Mansoor Saburov , Ashraf Mohamed Nawi

Represented spaces form the general setting for the study of computability derived from Turing machines. As such, they are the basic entities for endeavors such as computable analysis or computable measure theory. The theory of represented…

Logic · Mathematics 2015-03-04 Arno Pauly

This paper is a survey, with few proofs, of ideas and notions related to self-similarity of groups, semi-groups and their actions. It attempts to relate these concepts to more familiar ones, such as fractals, self-similar sets, and…

Group Theory · Mathematics 2009-11-29 Laurent Bartholdi , Rostislav I. Grigorchuk , Volodymyr V. Nekrashevych

In the era of big data, analysts usually explore various statistical models or machine learning methods for observed data in order to facilitate scientific discoveries or gain predictive power. Whatever data and fitting procedures are…

Machine Learning · Statistics 2018-10-24 Jie Ding , Vahid Tarokh , Yuhong Yang

Ideals are one of the main topics of interest to the study of the order structure of an algebra. Due to their nice properties, ideals have an important role both in lattice theory and semigroup theory. Two natural concepts of ideal can be…

Rings and Algebras · Mathematics 2013-02-25 Joao Pita Costa

We consider the set of all the ideals of a ring, endowed with the coarse lower topology. The aim of this paper is to study the topological properties of distinguished subspaces of this space and detect the spectrality of some of them.

Commutative Algebra · Mathematics 2024-08-21 Carmelo A. Finocchiaro , Amartya Goswami , Dario Spirito

The notion of concept drift refers to the phenomenon that the distribution generating the observed data changes over time. If drift is present, machine learning models can become inaccurate and need adjustment. While there do exist methods…

Machine Learning · Computer Science 2023-03-17 Fabian Hinder , Valerie Vaquet , Johannes Brinkrolf , Barbara Hammer

Exact string solutions are presented, providing backgrounds where a dynamical change of topology is occuring. This is induced by the time variation of a modulus field. Some lessons are drawn concerning the region of validity of effective…

High Energy Physics - Theory · Physics 2009-10-28 E. Kiritsis , C. Kounnas

We present a statistical mechanical theory of the process of annotating an object with terms selected from an ontology. The term selection process is formulated as an ideal lattice gas model, but in a highly structured inhomogeneous field.…

Physics and Society · Physics 2016-05-19 David C. Hoyle , Andrew Brass

Understanding how subsets of items are chosen from offered sets is critical to assortment planning, wireless network planning, and many other applications. There are two seemingly unrelated subset choice models that capture dependencies…

Machine Learning · Computer Science 2023-02-23 Sander Aarts , David B. Shmoys , Alex Coy

This note presents an attempt to provide a conceptual framework for variational formulations of classical physics. Variational principles of physics have all a common source in the {\it principle of virtual work} well known in statics of…

Mathematical Physics · Physics 2007-05-23 Wlodzimierz M. Tulczyjew

Networks of biochemical reactions, like cellular metabolic networks, are kept in non-equilibrium steady states by the exchange fluxes connecting them to the environment. In most cases, feasible flux configurations can be derived from…

Molecular Networks · Quantitative Biology 2014-12-01 Daniele De Martino , Fabrizio Capuani , Andrea De Martino

We derive computationally tractable methods to select a small subset of experiment settings from a large pool of given design points. The primary focus is on linear regression models, while the technique extends to generalized linear models…

Machine Learning · Statistics 2017-12-21 Yining Wang , Adams Wei Yu , Aarti Singh

Dynamical models of inflation are given with composite inflatons by means of massive supersymmetric gauge theory. Nearly flat directions and stable massive ones in the potential are identified and slow-roll during inflation is examined.…

High Energy Physics - Phenomenology · Physics 2008-11-26 K. Hamaguchi , K. -I. Izawa , H. Nakajima