A Theory-Based Evaluation of Nearest Neighbor Models Put Into Practice

no code implementations • NeurIPS 2018 • Hendrik Fichtenberger, Dennis Rohde

We study property testing of $k$-NN graphs in theory and evaluate it empirically: given a point set $P \subset \mathbb{R}^\delta$ and a directed graph $G=(P, E)$, is $G$ a $k$-NN graph, i. e., every point $p \in P$ has outgoing edges to its $k$ nearest neighbors, or is it $\epsilon$-far from being a $k$-NN graph?

Retrieval

Random Projections and Sampling Algorithms for Clustering of High-Dimensional Polygonal Curves

no code implementations • NeurIPS 2019 • Stefan Meintrup, Alexander Munteanu, Dennis Rohde

We study the $k$-median clustering problem for high-dimensional polygonal curves with finite but unbounded number of vertices.

Clustering