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It has been shown that uniform as well as non-uniform cellular automata (CA) can be evolved to perform certain computational tasks. Random Boolean networks are a generalization of two-state cellular automata, where the interconnection…

Disordered Systems and Neural Networks · Physics 2007-05-23 Bertrand Mesot , Christof Teuscher

Tumor development is an evolutionary process in which a heterogeneous population of cells with differential growth capabilities compete for resources in order to gain a proliferative advantage. What are the minimal ingredients needed to…

Populations and Evolution · Quantitative Biology 2016-01-19 Jeffrey West , Zaki Hasnain , Jeremy Mason , Paul K. Newton

The study of societies of adaptive agents seeking minority status is an active area of research. Recently, it has been demonstrated that such systems display an intriguing phase-transition: agents tend to {\it self-segregate} or to {\it…

Condensed Matter · Physics 2009-11-07 Ehud Nakar , Shahar Hod

For digital system designs, triple modular redundancy (TMR), which is a 3-tuple version of N-modular redundancy is widely preferred for many mission-control and safety-critical applications. The TMR scheme involves two-times duplication of…

Hardware Architecture · Computer Science 2017-11-09 P Balasubramanian , K Prasad

In this paper we give an asymptotically tight bound for the tolerated Tverberg Theorem when the dimension and the size of the partition are fixed. To achieve this we study certain partitions of order-type homogeneous sets and use a…

Combinatorics · Mathematics 2016-06-09 Natalia García-Colín , Miguel Raggi , Edgardo Roldán-Pensado

A new parameter choice rule for inverse problems is introduced. This parameter choice rule was developed for total variation regularization in electron tomography and might in general be useful for $L^1$ regularization of inverse problems…

Numerical Analysis · Mathematics 2008-04-28 Hans Rullgård

The simplest toroidally compactified string theories exhibit a duality between large and small radii: compactification on a circle, for example, is invariant under R goes to 1/R. Compactification on more general Lorentzian lattices (i.e.…

High Energy Physics - Theory · Physics 2010-11-01 Eva Silverstein

Living cells maintain size homeostasis by actively compensating for size fluctuations. Here, we present two stochastic maps that unify phenomenological models by integrating fluctuating single-cell growth rates and size-dependent noise…

Populations and Evolution · Quantitative Biology 2026-01-09 Arthur Genthon , Philipp Thomas

We study a \emph{Plurality-Consensus} process in which each of $n$ anonymous agents of a communication network initially supports an opinion (a color chosen from a finite set $[k]$). Then, in every (synchronous) round, each agent can revise…

Discrete Mathematics · Computer Science 2015-07-28 Luca Becchetti , Andrea Clementi , Emanuele Natale , Francesco Pasquale , Riccardo Silvestri , Luca Trevisan

In the standard minority game, every agent switches to his best strategy in hand at each time step. If only a small number of agents are allowed to switch their strategies at each time step, the population variance of the system plunges.…

Data Analysis, Statistics and Probability · Physics 2007-05-23 C. Liu , S. S. Liaw

We study binary opinion dynamics in a fully connected network of interacting agents. The agents are assumed to interact according to one of the following rules: (1) Voter rule: An updating agent simply copies the opinion of another randomly…

Probability · Mathematics 2022-03-04 Arpan Mukhopadhyay , Ravi R. Mazumdar , Rahul Roy

Neural networks produced by standard training are known to suffer from poor accuracy on rare subgroups despite achieving high accuracy on average, due to the correlations between certain spurious features and labels. Previous approaches…

Machine Learning · Computer Science 2024-04-10 Gaotang Li , Jiarui Liu , Wei Hu

A method is given for quantitatively rating the social acceptance of different options which are the matter of a preferential vote. In contrast to a previous article, here the individual votes are allowed to be incomplete, that is, they…

Optimization and Control · Mathematics 2012-03-09 Rosa Camps , Xavier Mora , Laia Saumell

Randomized smoothing, a method to certify a classifier's decision on an input is invariant under adversarial noise, offers attractive advantages over other certification methods. It operates in a black-box and so certification is not…

Machine Learning · Computer Science 2020-06-09 Jamie Hayes

Objects $T$ whose exponential functor $(-)^T$ admits a right adjoint $(-)_T$ are known under different names. The fact that they exist, yet that the only set that satisfies this in the category of sets is the singleton made Lawvere suggest…

Category Theory · Mathematics 2026-02-13 Enrique Ruiz Hernández , Pedro Solórzano

Numerical homogenization of multiscale equations typically requires taking an average of the solution to a microscale problem. Both the boundary conditions and domain size of the microscale problem play an important role in the accuracy of…

Numerical Analysis · Mathematics 2024-04-03 Sean P. Carney , Milica Dussinger , Bjorn Engquist

A method for studying exact properties of a class of {\it inhomogeneous} stochastic many-body systems is developed and presented in the framework of a voter model perturbed by the presence of a ``zealot'', an individual allowed to favour an…

Statistical Mechanics · Physics 2007-05-23 Mauro Mobilia

Cellular automata can show well known features of quantum mechanics, such as a linear rule according to which they evolve and which resembles a discretized version of the Schroedinger equation. This includes corresponding conservation laws.…

Quantum Physics · Physics 2016-04-25 Hans-Thomas Elze

The Central Limit Theorem states that, in the limit of a large number of terms, an appropriately scaled sum of independent random variables yields another random variable whose probability distribution tends to a stable distribution. The…

Data Analysis, Statistics and Probability · Physics 2024-04-08 Damián H. Zanette , Inés Samengo

Vote-boosting is a sequential ensemble learning method in which the individual classifiers are built on different weighted versions of the training data. To build a new classifier, the weight of each training instance is determined in terms…

Machine Learning · Computer Science 2018-02-22 Maryam Sabzevari , Gonzalo Martínez-Muñoz , Alberto Suárez
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