Network querying aims to search a large network for subnetwork regions that are similar to a given query network. In this paper, we propose a novel algorithm for querying large sc...
Given a set of n randomly drawn sample points, spectral clustering in its simplest form uses the second eigenvector of the graph Laplacian matrix, constructed on the similarity gra...
Ulrike von Luxburg, Olivier Bousquet, Mikhail Belk...
We explore the possibilities to organize a query data structure in the main memories or hard disks of a cluster computer. The query data structure serves to improve the performanc...
Abstract. In this paper we present a novel analysis of a random sampling approach for three clustering problems in metric spaces: k-median, min-sum kclustering, and balanced k-medi...
Reinforcement Learning research is traditionally devoted to solve single-task problems. Therefore, anytime a new task is faced, learning must be restarted from scratch. Recently, ...