Many machine learning algorithms for clustering or dimensionality reduction take as input a cloud of points in Euclidean space, and construct a graph with the input data points as...
Abstract. This paper is concerned with the reliable inference of optimal treeapproximations to the dependency structure of an unknown distribution generating data. The traditional ...
Hierarchical clustering methods are widely used in various scientific domains such as molecular biology, medicine, economy, etc. Despite the maturity of the research field of hie...
We study the complexity and the I/O-efficient computation of flow on triangulated terrains. We present an acyclic graph, the descent graph, that enables us to trace flow paths in ...
Mark de Berg, Otfried Cheong, Herman J. Haverkort,...
Most work on pattern mining focuses on simple data structures such as itemsets and sequences of itemsets. However, a lot of recent applications dealing with complex data like chem...
Sandra de Amo, Nyara A. Silva, Ronaldo P. Silva, F...