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The operation of adding edges has been frequently used to the study of opinion dynamics in social networks for various purposes. In this paper, we consider the edge addition problem for the DeGroot model of opinion dynamics in a social…

Social and Information Networks · Computer Science 2021-06-14 Xiaotian Zhou , Zhongzhi Zhang

Phenotypic variability in a population of cells can work as the bet-hedging of the cells under an unpredictably changing environment, the typical example of which is the bacterial persistence. To understand the strategy to control such…

Populations and Evolution · Quantitative Biology 2019-12-02 So Nakashima , Yuki Sughiyama , Tetsuya J. Kobayashi

Inside the discipline of graph theory exists an extension known as the hypergraph. This generalization of graphs includes vertices along with hyperedges consisting of collections of two or more vertices. One well-studied application of this…

Probability · Mathematics 2024-03-19 Joshua Sparks

Recently, Balliu, Brandt, and Olivetti [FOCS '20] showed the first $\omega(\log^* n)$ lower bound for the maximal independent set (MIS) problem in trees. In this work we prove lower bounds for a much more relaxed family of distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-06-07 Alkida Balliu , Sebastian Brandt , Fabian Kuhn , Dennis Olivetti

Phylogenetic networks are used to represent the evolutionary history of species. Recently, the new class of orchard networks was introduced, which were later shown to be interpretable as trees with additional horizontal arcs. This makes the…

Combinatorics · Mathematics 2023-05-09 Leo van Iersel , Mark Jones , Esther Julien , Yukihiro Murakami

Consider a committee election consisting of (i) a set of candidates who are divided into arbitrary groups each of size ${at~most}$ two and a diversity constraint that stipulates the selection of ${at~least}$ one candidate from each group…

Computational Complexity · Computer Science 2025-10-22 Kunal Relia

The recent emergence of extreme climate events has significantly raised awareness about sustainable living. In addition to developing energy-saving materials and technologies, existing research mainly relies on traditional methods that…

Information Retrieval · Computer Science 2025-08-20 Jiazheng Jing , Yinan Zhang , Chunyan Miao

A core tension in the study of plurality elections is the clash between the classic Hotelling-Downs model, which predicts that two office-seeking candidates should position themselves at the median voter's policy, and the empirical…

Computer Science and Game Theory · Computer Science 2025-03-04 Kiran Tomlinson , Tanvi Namjoshi , Johan Ugander , Jon Kleinberg

The probability of a given candidate winning a future election is worked out in closed form as a function of (i) the current support rates for each candidate, (ii) the relative positioning of the candidates within the political spectrum,…

Probability · Mathematics 2025-04-25 Dorje C. Brody , Tomooki Yuasa

We study a variant of decision-theoretic online learning in which the set of experts that are available to Learner can shrink over time. This is a restricted version of the well-studied sleeping experts problem, itself a generalization of…

Machine Learning · Computer Science 2019-10-31 Hamid Shayestehmanesh , Sajjad Azami , Nishant A. Mehta

An election is a pair $(C,V)$ of candidates and voters. Each vote is a ranking (permutation) of the candidates. An election is $d$-Euclidean if there is an embedding of both candidates and voters into $\mathbb{R}^d$ such that voter $v$…

Computer Science and Game Theory · Computer Science 2025-02-12 Michal Dvořák , Dušan Knop , Jan Pokorný , Martin Slávik

Citizens' assemblies are an increasingly influential form of deliberative democracy, where randomly selected people discuss policy questions. The legitimacy of these assemblies hinges on their representation of the broader population, but…

Machine Learning · Computer Science 2025-08-13 Angelos Assos , Carmel Baharav , Bailey Flanigan , Ariel Procaccia

Learning ensembles by bagging can substantially improve the generalization performance of low-bias, high-variance estimators, including those evolved by Genetic Programming (GP). To be efficient, modern GP algorithms for evolving (bagging)…

Neural and Evolutionary Computing · Computer Science 2021-02-08 Marco Virgolin

Choosing the placement of wildlife crossings (i.e., green bridges) to reconnect animal species' fragmented habitats is among the 17 goals towards sustainable development by the UN. We consider the following established model: Given a graph…

Data Structures and Algorithms · Computer Science 2022-01-31 Maike Herkenrath , Till Fluschnik , Francesco Grothe , Leon Kellerhals

We consider the problem of manipulating elections by cloning candidates. In our model, a manipulator can replace each candidate c by several clones, i.e., new candidates that are so similar to c that each voter simply replaces c in his vote…

Computer Science and Game Theory · Computer Science 2014-01-21 Edith Elkind , Piotr Faliszewski , Arkadii Slinko

Crossover is a powerful mechanism for generating new solutions from a given population of solutions. Crossover comes with a discrepancy in itself: on the one hand, crossover usually works best if there is enough diversity in the population;…

Neural and Evolutionary Computing · Computer Science 2025-07-03 Johannes Lengler , Tom Offermann

In an election, we are given a set of voters, each having a preference list over a set of candidates, that are distributed on a social network. We consider a scenario where voters may change their preference lists as a consequence of the…

Social and Information Networks · Computer Science 2020-06-01 Mohammad Abouei Mehrizi , Gianlorenzo D'Angelo

We consider the problem of protecting and manipulating elections by recounting and changing ballots, respectively. Our setting involves a plurality-based election held across multiple districts, and the problem formulations are based on the…

Computer Science and Game Theory · Computer Science 2020-11-24 Kishen N. Gowda , Neeldhara Misra , Vraj Patel

A Maximum Likelihood recursive state estimator is derived for non-linear and non-Gaussian state-space models. The estimator combines a particle filter to generate the conditional density and the Expectation Maximization algorithm to compute…

Methodology · Statistics 2021-03-22 Mohammad S. Ramadan , Robert R. Bitmead

The population protocol model is a computational model for passive mobile agents. We address the leader election problem, which determines a unique leader on arbitrary communication graphs starting from any configuration. Unfortunately,…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-11-10 Haruki Kanaya , Ryota Eguchi , Taisho Sasada , Michiko Inoue