arXiv Machine Learning

A General Framework for Dynamic Consistent Submodular Maximization

arXiv:2606. 04946v1 Announce Type: cross Abstract: Consistency is an important property in dynamic submodular maximization and entails maintaining a near-optimal solution at all times, making only a small number of adjustments to the solution in each step.

arXiv Machine Learning
Jul 3

Incremental (k, z)-Clustering on Graphs

arXiv:2602. 08542v3 Announce Type: replace-cross Abstract: Given a weighted undirected graph, a number of clusters $k$, and an exponent $z$, the goal in the $(k, z)$-clustering problem on graphs is to select $k$ vertices as centers that minimize the sum of the distances raised to the power $z$ of each vertex to its closest center.

By Emilio Cruciani, Sebastian Forster, Antonis Skarlatos