23 citations · 87 across the 20 of their papers we have counts for
4 papers · 1 filter
Random Sampling with Removal
Kenneth L. Clarkson, Bernd Gärtner, Johannes Lengler +1
We study randomized algorithms for constrained optimization, in abstract frameworks that include, in strictly increasing generality: convex programming; LP-type problems; violator…
Sampling Geometric Inhomogeneous Random Graphs in Linear Time
Karl Bringmann, Ralph Keusch, Johannes Lengler
Real-world networks, like social networks or the internet infrastructure, have structural properties such as large clustering coefficients that can best be described in terms of an…
Introducing Elitist Black-Box Models: When Does Elitist Selection Weaken the Performance of Evolutionary Algorithms?
Carola Doerr, Johannes Lengler
Black-box complexity theory provides lower bounds for the runtime of black-box optimizers like evolutionary algorithms and serves as an inspiration for the design of new genetic al…
OneMax in Black-Box Models with Several Restrictions
Carola Doerr, Johannes Lengler
Black-box complexity studies lower bounds for the efficiency of general-purpose black-box optimization algorithms such as evolutionary algorithms and other search heuristics. Diffe…