2 citations · 7 across the 11 of their papers we have counts for
12 papers
Degree-dependent and distance-dependent contact rates interpolate between explosive, exponential and polynomial epidemic growth
Zylan Benjert, Júlia Komjáthy, Johannes Lengler +2
It is a fundamental question in epidemiology to estimate, model and predict the growth rate of a pandemic. Analogously, analysing the diffusion of innovation, (fake) news, memes, a…
Assortativity in geometric and scale-free networks
Marc Kaufmann, Ulysse Schaller, Thomas Bläsius +1
The assortative behavior of a network is the tendency of similar (or dissimilar) nodes to connect to each other. This tendency can have an influence on various properties of the ne…
Expanders in Models of Social Networks
Marc Kaufmann, Johannes Lengler, Ulysse Schaller +1
A common model for social networks are Geometric Inhomogeneous Random Graphs (GIRGs), in which vertices draw a random position in some latent geometric space, and the probability o…
Balanced Bidirectional Breadth-First Search on Scale-Free Networks
Sacha Cerf, Benjamin Dayan, Umberto De Ambroggio +3
To find a shortest path between two nodes and in a given graph, a classical approach is to start a Breadth-First Search (BFS) from and run it until the search dis…
Rumour Spreading Depends on the Latent Geometry and Degree Distribution in Social Network Models
Marc Kaufmann, Kostas Lakis, Johannes Lengler +3
We study push-pull rumour spreading in ultra-small-world models for social networks where the degrees follow a power-law distribution. In a non-geometric setting, Fountoulakis, Pan…
Improved bounds for polylogarithmic graph distances in scale-free percolation and related models
Kostas Lakis, Johannes Lengler, Kalina Petrova +1
In this paper, we study graph distances in the geometric random graph models scale-free percolation SFP, geometric inhomogeneous random graphs GIRG, and hyperbolic random graphs HR…
Faster Optimization Through Genetic Drift
Cella Florescu, Marc Kaufmann, Johannes Lengler +1
The compact Genetic Algorithm (cGA), parameterized by its hypothetical population size , offers a low-memory alternative to evolving a large offspring population of solutions. I…
Self-Adjusting Evolutionary Algorithms Are Slow on Multimodal Landscapes
Johannes Lengler, Konstantin Sturm
The one-fifth rule and its generalizations are a classical parameter control mechanism in discrete domains. They have also been transferred to control the offspring population size…
Plus Strategies are Exponentially Slower for Planted Optima of Random Height
Johannes Lengler, Leon Schiller, Oliver Sieberling
We compare the -EA and the -EA on the recently introduced benchmark DisOM, which is the OneMax function with randomly planted local optima. Previous work showed tha…
Hardest Monotone Functions for Evolutionary Algorithms
Marc Kaufmann, Maxime Larcher, Johannes Lengler +1
In this paper we revisit the question how hard it can be for the Evolutionary Algorithm to optimize monotone pseudo-Boolean functions. By introducing a more pessimistic sto…
Polynomial growth in degree-dependent first passage percolation on spatial random graphs
Júlia Komjáthy, John Lapinskas, Johannes Lengler +1
In this paper we study a version of (non-Markovian) first passage percolation on graphs, where the transmission time between two connected vertices is non-iid, but increases by a p…
Four universal growth regimes in degree-dependent first passage percolation on spatial random graphs I
Júlia Komjáthy, John Lapinskas, Johannes Lengler +1
One-dependent first passage percolation is a spreading process on a graph where the transmission time through each edge depends on the direct surroundings of the edge. In particula…