133 citations · 336 across the 8 of their papers we have counts for
8 papers
We Need Explanation Cards to Connect Explanation Algorithms to the Real World
Eric Günther, Balázs Szabados, Kristof Meding +3
Algorithmic explanations are intended to help stakeholders understand opaque algorithmic decisions, but in practice, they often fall short. First, the meaning of algorithmic explan…
ChatGPT Participates in a Computer Science Exam
Sebastian Bordt, Ulrike von Luxburg
We asked ChatGPT to participate in an undergraduate computer science exam on ''Algorithms and Data Structures''. The program was evaluated on the entire exam as posed to the studen…
Clustering with Tangles: Algorithmic Framework and Theoretical Guarantees
Solveig Klepper, Christian Elbracht, Diego Fioravanti +4
Originally, tangles were invented as an abstract tool in mathematical graph theory to prove the famous graph minor theorem. In this paper, we showcase the practical potential of ta…
Consistent procedures for cluster tree estimation and pruning
Kamalika Chaudhuri, Sanjoy Dasgupta, Samory Kpotufe +1
For a density on , a {\it high-density cluster} is any connected component of , for some . The set of all high-density clusters forms a…
Clustering Stability: An Overview
Ulrike von Luxburg
A popular method for selecting the number of clusters is based on stability arguments: one chooses the number of clusters such that the corresponding clustering results are "most s…
Hitting and commute times in large graphs are often misleading
Ulrike von Luxburg, Agnes Radl, Matthias Hein
Next to the shortest path distance, the second most popular distance function between vertices in a graph is the commute distance (resistance distance). For two vertices u and v, t…
Optimal construction of k-nearest neighbor graphs for identifying noisy clusters
Markus Maier, Matthias Hein, Ulrike von Luxburg
We study clustering algorithms based on neighborhood graphs on a random sample of data points. The question we ask is how such a graph should be constructed in order to obtain opti…
A Geometric Approach to Confidence Sets for Ratios: Fieller's Theorem, Generalizations, and Bootstrap
Ulrike von Luxburg, Volker H. Franz
We present a geometric method to determine confidence sets for the ratio E(Y)/E(X) of the means of random variables X and Y. This method reduces the problem of constructing confide…